From 5-Pass \(\mathcal {MQ}\)-Based Identification to \(\mathcal {MQ}\)-Based Signatures

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10032)


This paper presents MQDSS, the first signature scheme with a security reduction based on the problem of solving a multivariate system of quadratic equations (\(\mathcal {MQ}\) problem). In order to construct this scheme we give a new security reduction for the Fiat-Shamir transform from a large class of 5-pass identification schemes and show that a previous attempt from the literature to obtain such a proof does not achieve the desired goal. We give concrete parameters for MQDSS and provide a detailed security analysis showing that the resulting instantiation MQDSS-31-64 achieves 128 bits of post-quantum security. Finally, we describe an optimized implementation of MQDSS-31-64 for recent Intel processors with full protection against timing attacks and report benchmarks of this implementation.


Post-quantum cryptography Fiat-Shamir 5-pass identification scheme Vectorized implementation 

1 Introduction

Already since 1997, when Shor published a polynomial-time quantum algorithm for factoring and discrete logarithms, it is known that an attacker equipped with a sufficiently large quantum computer will be able to break essentially all public-key cryptography in use today. More recently, various statements by physicists and quantum engineers indicate that they may be able to build such a large quantum computer within the next few decades. For example, IBM’s Mark Ketchen said in 2012 “I’m thinking like it’s 15 [years] or a little more. It’s within reach. It’s within our lifetime. It’s going to happen.”. In May this year, IBM gave access to their 5-qubit quantum computer to researchers and announced that they are expecting to scale up to 50–100 qubits within one decade [36].

It is still a matter of debate when and even if we will see a large quantum computer that can efficiently break, for example, RSA-4096 or 256-bit elliptic-curve crypto. However, it becomes more and more clear that cryptography aiming at long-term security can no longer discard the possibility of attacks by large quantum computers in the foreseeable future. Consequently, NSA recently updated their Suite B to explicitly emphasize the importance of a migration to post-quantum algorithms [41] and NIST announced a call for submissions to a post-quantum competition [40]. Submissions to this competition will be accepted for post-quantum public-key encryption, key exchange, and digital signature. The results presented in this paper fall into the last of these three categories: post-quantum digital signature schemes.

Most experts agree that the most conservative choice for post-quantum signatures are hash-based signatures with tight reductions in the standard model to properties like second-preimage resistance of an underlying cryptographic hash function. Unfortunately, the most efficient hash-based schemes are stateful, a property that makes their use prohibitive in many scenarios [39]. A reasonably efficient stateless construction called SPHINCS was presented at Eurocrypt 2015 [6]; however, eliminating the state in this scheme comes at the cost of decreased speed and increased signature size.

The second direction of research for post-quantum signatures are lattice-based schemes. Various schemes have been proposed with different security and performance properties. The best performance is achieved by BLISS [23] (improved in [22]) whose security reduction relies on the hardness of R-SIS and NTRU, and is non-tight. Furthermore, the performance is achieved at the cost of being vulnerable against cache-attacks as demonstrated in [33]. A more conservative approach is the signature scheme proposed by Bai and Galbraith in [3] with improvements to performance and security in [1, 2, 17]. The security reduction to LWE in [2] is tight; a variant using the (more efficient) ideal-lattice setting was presented in [1]. However, these schemes either come with enormous key and signature sizes (e.g. sizes in [2] are in the order of megabytes), or sizes are reduced at the cost of switching to assumptions on lattices with additional structure like NTRU, Ring-SIS, or Ring-LWE.

The third large class of post-quantum signature algorithms is based on the hardness of solving large systems of multivariate quadratic equations, the so-called \(\mathcal {MQ}\) problem. For random instances this problem is NP-complete [30]. However, all schemes in this class that have been proposed with actual parameters for practical use share two properties that often raise concerns about their security: First, their security arguments are rather ad-hoc; there is no reduction from the hardness of \(\mathcal {MQ}\). The reason for this is the second property, namely that these systems require a hidden structure in the system of equations; this implies that their security inherently also relies on the hardness of the so-called isomorphism-of-polynomials (IP) problem [42] (or, more precisely, the Extended IP problem [19] or the similar IP with partial knowledge [51] problem). Time has shown that IP in many of the proposed schemes actually relies on the MinRank problem [16, 28], and unfortunately, more than often, on an easy instance of this problem. Therefore, many proposed schemes have been broken not by targeting \(\mathcal {MQ}\), but by targeting IP (and thus exploiting the structure in the system of equations). Examples of broken schemes include Oil-and-Vinegar [43] (broken in [38]), SFLASH [14] (broken in [21]), MQQ-Sig [31] (broken in [27]), (Enhanced) TTS [57, 58] (broken in [52]), and Enhanced STS [53] (broken in [52]). There are essentially only two proposals from the “\(\mathcal {MQ}\) + IP” class of schemes that are still standing: HFEv\(^-\) variants [44, 45] and Unbalanced Oil-and-Vinegar (UOV)variants [20, 37]. The literature does not, to the best of our knowledge, describe any instantiation of those schemes with parameters that achieve a conservative post-quantum security level.

Contributions of this paper. Obviously what one would want in the realm of \(\mathcal {MQ}\)-based signatures is a scheme that has a tight reduction to \(\mathcal {MQ}\) in the quantum-random-oracle model (QROM) or even better in the standard model, and has small key and signatures sizes and fast signing and verification algorithms when instantiated with parameters that offer 128 bits of post-quantum security. In this paper we make a major step towards such a scheme. Specifically, we present a signature system with a reduction from \(\mathcal {MQ}\), a set of parameters that achieves 128 bits of post-quantum security according to our careful post-quantum security analysis, and an optimized implementation of this scheme.

This does not mean that our proposal is going quite all the way to the desired scheme sketched above: our reduction is non-tight and in the ROM. Furthermore, at the 128-bit post-quantum security level, the signature size is 40 952 bytes, which is comparable to SPHINCS [6], but larger than what lattice-based schemes or \(\mathcal {MQ}\) + IP schemes achieve. However, the scheme excels in key sizes: it needs only 72 bytes for public keys and 64 bytes for private keys.

The basic idea of our construction is to apply a Fiat-Shamir transform to the \(\mathcal {MQ}\)-based 5-pass identification scheme (IDS) that was presented by Sakumoto, Shirai, and Hiwatari at Crypto 2011 [48]. In principle, this idea is not new; it already appeared in a 2012 paper by El Yousfi Alaoui, Dagdelen, Véron, Galindo, and Cayrel [24]. In their paper they use the 5-pass IDS from [48] as one example of a scheme with a property they call “n-soundness”. According to their proof in the ROM, this property of an IDS guarantees that it can be used in a Fiat-Shamir transform to obtain an existentially unforgeable signature scheme. They give such a transform using the IDS from [48, Sect. 4.2].

One might think that choosing suitable parameters for precisely this transform (and implementing the scheme with those parameters) produces the results we are advertising in this paper. However, we show that not only is the construction from [24, Sect. 4.2] insecure (because it ignores the requirement of an exponentially large challenge space), but also that the proof based on the n-soundness property does not apply to a corrected Fiat-Shamir transform of the 5-pass IDS from [48]. The reason is that the n-soundness property does not hold for this IDS. More than that, we show that any \((2n+1)\)-pass scheme for which the n-soundness property holds can trivially be transformed into a 3-pass scheme. This observation essentially renders the results of [24] vacuous, because the declared contribution of that paper is to present “the first transformation which gives generic security statements for SS derived from \((2n+1)\) -pass IS”.

To solve these issues, we present a new proof in the ROM for Fiat-Shamir transforms of a large class of 5-pass IDS, including the 5-pass scheme from [48]. This proof is of independent interest; it applies also, for example, to the IDS from [11, 49] and (with minor modifications) to [46]. Equipped with this result, we fix the signature scheme from [24] and instantiate the scheme with parameters for the 128-bit post-quantum security level. We call this signature scheme MQDSS and the concrete instatiation with the proposed parameters MQDSS-31-64. Our optimized implementation of MQDSS-31-64 for Intel Haswell processors takes 8 510 616 cycles for signing and 5 752 612 cycles for verification; key generation takes 1 826 612 cycles. These cycle counts include full protection against timing attacks.

Organization of this paper. We start with some preliminaries in Sect. 2. In Sect. 3, we recall the 5-pass IDS as introduced in [48]. We present our theoretical results in Sect. 4. We discuss the problems with the result from [24] in Subsect. 4.1, and resolve them by providing a new proof in Subsect. 4.3. We present a description of the transformed 5-pass signature scheme and give a security reduction for it in Sect. 5. In Sect. 6 we finally present a concrete instantiation and implementation thereof.

Availability of the software. We place all software described in this paper into the public domain to maximize reusability of our results. The software is available online at

2 Preliminaries

In the following we provide basic definitions used throughout this work.

Digital signatures. The main target of this work are digital signature schemes. These are defined as follows.

Definition 2.1

(Digital signature scheme). A digital signature scheme \(\mathsf {\textsf {Dss}}\) is a triplet of polynomial time algorithms \(\mathsf {\textsf {Dss}}= (\mathsf {KGen},\mathsf {Sign},\mathsf {Vf})\) defined as:
  • The key generation algorithm \(\mathsf {KGen} \) is a probabilistic algorithm that on input \(1^k\), where k is a security parameter, outputs a key pair \((\mathsf {sk},\mathsf {pk})\).

  • The signing algorithm \(\mathsf {Sign} \) is a possibly probabilistic algorithm that on input a secret key \(\mathsf {sk} \) and a message M outputs a signature \(\sigma \).

  • The verification algorithm \(\mathsf {Vf} \) is a deterministic algorithm that on input a public key \(\mathsf {pk} \), a message M and a signature \(\sigma \) outputs a bit b, where \(b=1\) indicates that the signature is accepted and \(b=0\) indicates a reject.

For correctness of a \(\mathsf {\textsf {Dss}}\), we require that for all \(k \in \mathbb {N}\), \((\mathsf {sk},\mathsf {pk})\leftarrow \mathsf {KGen} (1^k)\), all messages M and all signatures \(\sigma \leftarrow \mathsf {Sign} (\mathsf {sk},M)\), we get \(\mathsf {Vf} (\mathsf {pk}, M,\sigma )=1\), i.e., that correctly generated signatures are accepted.

Existential Unforgeability under Adaptive Chosen Message Attacks. The standard security notion for digital signature schemes is existential unforgeability under adaptive chosen message attacks (\(\mathsf {\textsf {{EU\text {-}CMA}}}\)) [32] which is defined using the following experiment. By \(\mathsf {\textsf {Dss}}(1^k)\) we denote a signature scheme with security parameter k.
For the success probability of an adversary \(\mathcal {A} \) in the above experiment we write
$$\begin{aligned} {\mathrm {Succ}}^{{{\mathsf {\textsf {{eu\text {-}cma}}}}}}_{\mathsf {\textsf {Dss}}(1^k)}\left( {\mathcal {A}} \right) = \mathsf {Pr}\left[ \mathsf {Exp}^{\mathsf {\textsf {{eu\text {-}cma}}}}_{\mathsf {\textsf {Dss}}(1^k)}(\mathcal {A}) = 1\right] . \end{aligned}$$
A signature scheme is called \(\mathsf {\textsf {{EU\text {-}CMA}}}\)-secure if any PPT adversary has only negligible success probability:

Definition 2.2

( EU-CMA ). Let \(k \in \mathbb {N}\), \(\mathsf {\textsf {Dss}}\) a digital signature scheme as defined above. We call \(\mathsf {\textsf {Dss}}\) \(\mathsf {\textsf {{EU\text {-}CMA}}}\)-secure if for all \(Q_s,t = \text {poly}{(k)}\) the maximum success probability \({\mathrm {InSec}}^{{\mathsf {\textsf {{eu\text {-}cma}}}}}\left( {\mathsf {\textsf {Dss}}(1^k)}; {t,Q_s} \right) \) of all possibly probabilistic classical adversaries \(\mathcal {A} \) running in time \(\le t\), making at most \(Q_s\) queries to \(\mathsf {Sign}\) in the above experiment, is negligible in k:
$$\begin{aligned} {\mathrm {InSec}}^{{\mathsf {\textsf {{eu\text {-}cma}}}}}\left( {\mathsf {\textsf {Dss}}(1^k)}; {t,Q_s} \right) \mathop {=}\limits ^{def}\max _{\mathcal {A}} \{{\mathrm {Succ}}^{{{\mathsf {\textsf {{eu\text {-}cma}}}}}}_{\mathsf {\textsf {Dss}}(1^k)}\left( {\mathcal {A}} \right) \} = \text {negl}{(k)}. \end{aligned}$$

Identification Schemes. An identification scheme (IDS) is a protocol that allows a prover \(\mathcal {P} \) to convince a verifier \(\mathcal {V} \) of its identity. More formally this is covered by the following definition.

Definition 2.3

(Identification scheme). An identification scheme consists of three probabilistic, polynomial-time algorithms \(\mathsf {IDS} = (\mathsf {KGen}, \mathcal {P}, \mathcal {V})\) such that:
  • the key generation algorithm \(\mathsf {KGen} \) is a probabilistic algorithm that on input \(1^k\), where k is a security parameter, outputs a key pair \((\mathsf {sk},\mathsf {pk})\).

  • \(\mathcal {P}\) and \(\mathcal {V}\) are interactive algorithms, executing a common protocol. The prover \(\mathcal {P}\) takes as input a secret key \(\mathsf {sk}\) and the verifier \(\mathcal {V}\) takes as input a public key \(\mathsf {pk}\). At the conclusion of the protocol, \(\mathcal {V}\) outputs a bit b with \(b = 1\) indicating “accept” and \(b = 0\) indicating “reject”.

For correctness of the scheme we require that for all \(k\in \mathbb {N}\) and all \((\mathsf {pk}, \mathsf {sk}) \leftarrow \mathsf {KGen} (1^k)\) we have \(\mathsf {Pr}\left[ \left\langle \mathcal {P} (\mathsf {sk}), \mathcal {V} (\mathsf {pk})\right\rangle = 1\right] = 1,\) where \(\left\langle \mathcal {P} (\mathsf {sk}), \mathcal {V} (\mathsf {pk})\right\rangle \) refers to the common execution of the protocol between \(\mathcal {P}\) with input \(\mathsf {sk}\) and \(\mathcal {V}\) on input \(\mathsf {pk}\).

In this work we are only concerned with passively secure identification schemes. We define security in terms of two properties: soundness and honest-verifier zero-knowledge.

Definition 2.4

(Soundness (with soundness error \(\kappa \) )). Let \(k \in \mathbb {N}\), \(\mathsf {IDS} = (\mathsf {KGen}, \mathcal {P}, \mathcal {V})\) an identification scheme. We say that \(\mathsf {IDS} \) is sound with soundness error \(\kappa \) if for every PPT adversary \(\mathcal {A}\),
$$\begin{aligned} \mathsf {Pr}\left[ \begin{array}{l} (\mathsf {pk},\mathsf {sk}) \leftarrow \mathsf {KGen} (1^k) \\ \left\langle \mathcal {A} (1^k,\mathsf {pk}), \mathcal {V} (\mathsf {pk})\right\rangle = 1 \end{array} \right] \le \kappa + \text {negl}{(k)}. \end{aligned}$$

Of course, the goal is to obtain an IDS with negligible soundness error. This can be achieved by running r rounds of the protocol for an r that fulfills \(\kappa ^r = \text {negl}{(k)}\).

For the following definition we need the notion of a transcript. A transcript of an execution of an identification scheme \(\mathsf {IDS}\) refers to all the messages exchanged between \(\mathcal {P}\) and \(\mathcal {V}\) and is denoted by \(\mathsf {trans} (\left\langle \mathcal {P} (\mathsf {sk}), \mathcal {V} (\mathsf {pk})\right\rangle )\).

Definition 2.5

((statistical) Honest-verifier zero-knowledge). Let \(k \in \mathbb {N}\), \(\mathsf {IDS} = (\mathsf {KGen}, \mathcal {P}, \mathcal {V})\) an identification scheme. We say that \(\mathsf {IDS} \) is statistical honest-verifier zero-knowledge if there exists a probabilistic polynomial time algorithm \(\mathcal {S} \), called the simulator, such that the statistical distance between the following two distribution ensembles is negligible in k:
$$\begin{aligned}&\left\{ (\mathsf {pk},\mathsf {sk}) \leftarrow \mathsf {KGen} (1^k): \left( \mathsf {sk},\mathsf {pk},\mathsf {trans} (\left\langle \mathcal {P} (\mathsf {sk}), \mathcal {V} (\mathsf {pk})\right\rangle )\right) \right\} \\&\left\{ (\mathsf {pk},\mathsf {sk}) \leftarrow \mathsf {KGen} (1^k): \left( \mathsf {sk},\mathsf {pk},\mathcal {S} (\mathsf {pk})\right) \right\} . \end{aligned}$$

3 Sakumoto et al. 5-Pass IDS Scheme

In [48], Sakumoto et al. proposed two new identification schemes, a 3-pass and a 5-pass IDS, based on the intractability of the \(\mathcal {MQ}\) problem. They showed that assuming existence of a non-interactive commitment scheme that is statistically hiding and computationally binding, their schemes are statistical zero knowledge and argument of knowledge, respectively. They further showed that the parallel composition of their protocols is secure against impersonation under passive attack. Let us quickly recall the basics of the construction.

Let \(\mathbf {x}=(x_1,\dots ,x_n)\) and let \(\mathcal {MQ} (n,m,\mathbb {F}_q)\) denote the family of vectorial functions \(\mathbf F :\mathbb {F}_q^n\rightarrow \mathbb {F}_q^m\) of degree 2 over \(\mathbb {F}_q\): \(\mathcal {MQ} (n,m,\mathbb {F}_q)=\{ \mathbf F (\mathbf {x})=(f_1(\mathbf {x}),\dots ,f_m(\mathbf {x}))| f_s(\mathbf {x})=\sum _{i,j}{a^{(s)}_{i,j}x_ix_j}+ \sum _{i}{b^{(s)}_ix_i}, s\in \{1,\dots ,m\} \}\). The function \(\mathbf G (\mathbf{x},\mathbf{y})=\mathbf F (\mathbf{x}+\mathbf{y})-\mathbf F (\mathbf{x})-\mathbf F (\mathbf{y})\) is called the polar form of the function \(\mathbf F \). The \(\mathcal {MQ}\) problem \(\mathcal {MQ} (\mathbf F ,\mathbf {v})\) is defined as follows:

Given \(\mathbf {v}\in \mathbb {F}_q^m\) find, if any, \(\mathbf {s}\in \mathbb {F}_q^n\) such that \(\mathbf F (\mathbf {s})=\mathbf {v}\).

The decisional version of this problem is \(\mathsf {NP}\text {-}\)complete [30]. It is widely believed that the \(\mathcal {MQ}\) problem is intractable, i.e., that given \(\mathbf F \leftarrow _R\mathcal {MQ} (n,m,\mathbb {F}_q)\), \(\mathbf {s}\leftarrow _R\mathbb {F}_q^n\) and \(\mathbf {v}=\mathbf F (\mathbf {s})\) there does not exist a PPT adversary \(\mathcal {A}\) that outputs a solution \(\mathbf {s}'\) to the \(\mathcal {MQ} (\mathbf F ,\mathbf {v})\) problem with non-negligible probability.

The novelty of the approach of Sakumoto et al. [48] is that unlike previous public key schemes, their solution provably relies only on the \(\mathcal {MQ}\) problem (and the security of the commitment scheme), and not on other related problems in multivariate cryptography such as the Isomorphism of Polynomials (IP) problem [42], the related Extended IP [19] and IP with partial knowledge [51] problems or the MinRank problem [16, 28]. The key for this is the introduction of a technique to split the secret using the polar form \(\mathbf G (\mathbf {x},\mathbf {y})\) of a system of polynomials \(\mathbf F (\mathbf {x})\).

In essence, with their technique, the secret \(\mathbf s \) is split into \(\mathbf s =\mathbf r _0+\mathbf r _1\), and the public \(\mathbf v = \mathbf F (\mathbf s )\) can be represented as \(\mathbf v =\mathbf F (\mathbf r _0)+\mathbf F (\mathbf r _1)+\mathbf G (\mathbf r _0,\mathbf r _1)\). In order for the polar form not to depend on both shares of the secret, \(\mathbf r _0\) and \(\mathbf F (\mathbf r _0)\) are further split as \(\alpha \mathbf r _0=\mathbf t _0+\mathbf t _1\) and \(\alpha \mathbf F (\mathbf r _0)=\mathbf e _0+\mathbf e _1\). Now, due to the linearity of the polar form it holds that \(\alpha \mathbf v =(\mathbf e _1 + \alpha \mathbf F (\mathbf r _1) + \mathbf G (\mathbf t _1, \mathbf r _1)) + (\mathbf e _0 + \mathbf G (\mathbf t _0, \mathbf r _1))\), and from only one of the two summands, represented by \((\mathbf r _1, \mathbf t _1, \mathbf e _1)\) and \((\mathbf r _1, \mathbf t _0, \mathbf e _0)\), nothing can be learned about the secret \(\mathbf s \). The 5-pass IDS is given in Fig. 1 where \((\mathsf {pk},\mathsf {sk})=(\mathbf {v},\mathbf {s}) \leftarrow \mathsf {KGen} (\mathbf{1}^\mathbf{k})\).
Fig. 1.

Sakumoto et al. 5-pass IDS

Sakumoto et al. [48] proved that their 5-pass scheme is statistically zero knowledge when the commitment scheme Com is statistically hiding which implies (honest-verifier) zero knowledge. Here we prove the soundness property of the scheme1.

Theorem 3.1

The 5-pass identification scheme of Sakumoto et al. [48] is sound with soundness error \(\frac{1}{2}+\frac{1}{2q}\) when the commitment scheme Com is computationally binding.


One can show that there exists an adversary \(\mathcal {C}\) that can cheat with probability \(\frac{1}{2}+\frac{1}{2q}\) (See the full version [13]). What we want to show now is that there cannot exist a cheater that wins with significantly higher success probability as long as the \(\mathcal {MQ}\) problem is hard and the used commitment is computationally binding.

Towards a contradiction, suppose there exists a malicious PPT cheater \(\mathcal {C} \) such that it holds that \(\epsilon := \mathsf {Pr}[\left\langle \mathcal {C} (1^k,\mathbf {v}), \mathcal {V} (\mathbf {v})\right\rangle = 1] - (\frac{1}{2}+\frac{1}{2q}) = \frac{1}{P(k)}.\) for some polynomial function P(k). We show that this implies that there exists a PPT adversary \(\mathcal {A}\) with access to \(\mathcal {C} \) that can either break the binding property of Com or can solve the \(\mathcal {MQ}\) problem \(\mathcal {MQ} (\mathbf {F},\mathbf {v})\).

\(\mathcal {A}\) can achieve this if she can obtain four accepting transcripts from \(\mathcal {C} \) with same internal random tape, equation system \(\mathbf {F}\), and public key \(\mathbf {v}\), such that for two different \(\alpha \) there are two transcripts for each \(\alpha \) with different \(\mathsf {ch} _2\). This is done by rewinding \(\mathcal {C} \) and feeding it with all possible combinations of \(\alpha \in [0,q-1]\) and \(ch_2\in \{0,1\}\). That way we obtain 2q different transcripts. Now, per assumption \(\mathcal {C} \) produces an accepting transcript with probability \(\frac{1}{2}+\frac{1}{2q} + \epsilon \). Hence, with non-negligible probability \(\epsilon \) we get at least \(q+2\) accepting transcripts. A simple counting argument gives that there has to be a set of four transcripts fulfilling the above conditions. Let these transcripts be \(((c_0,c_1),\alpha ^{(i)}, (\mathbf {t}_1^{(i)},\mathbf {e}_1^{(i)}),\mathsf {ch} _2^{(i)},\mathsf {resp} _2^{(i)})\), where \(\alpha ^{(1)}=\alpha ^{(2)} \ne \alpha ^{(3)}=\alpha ^{(4)}\), \(\mathbf {t}_1^{(1)}=\mathbf {t}_1^{(2)} \ne \mathbf {t}_1^{(3)}=\mathbf {t}_1^{(4)}\), \(\mathbf {e}_1^{(1)} = \mathbf {e}_1^{(2)} \ne \mathbf {e}_1^{(3)} = \mathbf {e}_1^{(4)}\), \(\mathsf {ch} _2^{(1)} = \mathsf {ch} _2^{(3)} = 0\), \(\mathsf {ch} _2^{(2)} = \mathsf {ch} _2^{(4)} = 1\), \(\mathsf {resp} _2^{(1)} = \mathbf {r}_0^{(1)}\), \(\mathsf {resp} _2^{(3)} = \mathbf {r}_0^{(3)}\), \(\mathsf {resp} _2^{(2)} = \mathbf {r}_1^{(2)}\), \(\mathsf {resp} _2^{(4)} = \mathbf {r}_1^{(4)}\). Since the commitment \((c_0,c_1)\) is the same in all four transcripts, we have
$$\begin{aligned} \begin{array}{c} Com(\mathbf r _0^{(1)},\alpha ^{(1)} \mathbf r ^{(1)}_0-\mathbf t ^{(1)}_1,\alpha ^{(1)} \mathbf F (\mathbf r ^{(1)}_0)-\mathbf e ^{(1)}_1)=\\ Com(\mathbf r ^{(3)}_0,\alpha ^{(3)} \mathbf r ^{(3)}_0-\mathbf t ^{(3)}_1,\alpha ^{(3)} \mathbf F (\mathbf r ^{(3)}_0)-\mathbf e ^{(3)}_1)\ \end{array} \end{aligned}$$
$$\begin{aligned} \begin{array}{c} Com(\mathbf r ^{(2)}_1,\alpha ^{(2)} (\mathbf v -\mathbf F (\mathbf r ^{(2)}_1))-\mathbf G (\mathbf t ^{(2)}_1,\mathbf r ^{(2)}_1)-\mathbf e ^{(2)}_1)=\\ Com(\mathbf r ^{(4)}_1,\alpha ^{(4)} (\mathbf v -\mathbf F (\mathbf r ^{(4)}_1))-\mathbf G (\mathbf t ^{(4)}_1,\mathbf r ^{(4)}_1)-\mathbf e ^{(4)}_1)\ \end{array} \end{aligned}$$
If any of the arguments of Com on the left-hand side is different from the one on the right-hand side in (1) or in (2), then we get two different openings of Com, which breaks its computationally binding property.

If they are the same in both (1) and (2), then from (1):

\(\begin{array}{c} (\alpha ^{(1)}-\alpha ^{(3)}) \mathbf r ^{(1)}_0=\mathbf t ^{(1)}_1-\mathbf t ^{(3)}_1\ \mathrm{and}\ (\alpha ^{(1)}-\alpha ^{(3)})\mathbf F (\mathbf r ^{(1)}_0)=\mathbf e ^{(1)}_1-\mathbf e ^{(3)}_1\ \end{array},\)

and from (2): \( (\alpha ^{(2)}-\alpha ^{(4)}) (\mathbf v -\mathbf F (\mathbf r ^{(2)}_1))= \mathbf G (\mathbf t ^{(2)}_1-\mathbf t ^{(4)}_1,\mathbf r ^{(2)}_1)+\mathbf e ^{(2)}_1-\mathbf e ^{(4)}_1\).

Combining the two,
$$\begin{aligned} (\alpha ^{(2)}-\alpha ^{(4)}) (\mathbf v -\mathbf F (\mathbf r ^{(2)}_1))= (\alpha ^{(2)}-\alpha ^{(4)})\mathbf G (\mathbf r ^{(1)}_0,\mathbf r ^{(2)}_1)+(\alpha ^{(2)}-\alpha ^{(4)})\mathbf F (\mathbf r ^{(1)}_0), \end{aligned}$$
and since \(\alpha ^{(2)}\ne \alpha ^{(4)}\) we get \(\mathbf v =\mathbf F (\mathbf r ^{(2)}_1)+ \mathbf G (\mathbf r ^{(1)}_0,\mathbf r ^{(2)}_1)+\mathbf F (\mathbf r ^{(1)}_0),\) i.e., \(\mathbf r ^{(1)}_0+\mathbf r ^{(2)}_1\) is a solution to the given \(\mathcal {MQ}\) problem.    \(\square \)

We will look into the inner workings of the IDS in more detail in Sect. 5, where we also introduce the related 3-pass scheme.

4 Fiat-Shamir for 5-Pass Identification Schemes

For several intractability assumptions, the most efficient IDS are five pass, i.e. IDS where a transcript consists of five messages. Here, efficiency refers to the size of all communication of sufficient rounds to make the soundness error negligible. This becomes especially relevant when one wants to turn an IDS into a signature scheme as it is closely related to the signature size of the resulting scheme.

In [24], the authors present a Fiat-Shamir style transform for \((2n+1)\)-pass IDS fulfilling a certain kind of canonical structure. To provide some intuition, a five pass IDS is called canonical in the above sense if \(\mathcal {P}\) starts with a commitment \(\mathsf {com} _1\), \(\mathcal {V}\) replies with a challenge \(\mathsf {ch} _1\), \(\mathcal {P}\) sends a first response \(\mathsf {resp} _1\), \(\mathcal {V}\) replies with a second challenge \(\mathsf {ch} _2\) and finally \(\mathcal {P}\) returns a second response \(\mathsf {resp} _2\). Based on this transcript, \(\mathcal {V}\) then accepts or rejects. The authors of [24] also present a security reduction for signature schemes derived from such IDS using a security property of the IDS which they call special n-soundness. Intuitively, this property says that given two transcripts that agree on all messages but the last challenge and possibly the last response, one can extract a valid secret key.

In this section we first show that any \((2n+1)\)-pass IDS that fulfills the requirements of the security reduction in [24] can be converted into a 3-pass IDS by letting \(\mathcal {P}\) choose all but the last challenge uniformly at random himself. The main reason this is possible is the special n-soundness. On the other hand, we argue that existing 5-pass schemes in the literature do not fulfill special n-soundness and prove it for the 5-pass \(\mathcal {MQ}\)-IDS from [48]. Hence, they can neither be turned into 3-pass schemes, nor does the security reduction from [24] apply. Afterwards we give a security reduction for a less generic class of 5-pass IDS which covers many 5-pass IDS, including [11, 46, 49]. In particular, it covers the 5-pass \(\mathcal {MQ}\) scheme from [48].

4.1 The El Yousfi et al. Proof

Before we can make any statement about IDS that fall into the case of [24] we have to define the target of our analysis. A canonical \((2n+1)\)-pass IDS is an IDS where the prover and the verifier exchange n challenges and replies. More formally:

Definition 4.1

(Canonical \((2n+1)\) -pass identification schemes). Let \(k \in \mathbb {N}\), \(\mathsf {IDS} = (\mathsf {KGen},\mathcal {P},\mathcal {V})\) a \((2n+1)\)-pass identification scheme with n challenge spaces \(\mathsf {C} _j, 0 < j \le n\). We call \(\mathsf {IDS}\) a canonical \((2n+1)\)-pass identification scheme if the prover can be split into \(n+1\) subroutines \(\mathcal {P} = (\mathcal {P} _0, \ldots , \mathcal {P} _n)\) and the verifier into \(n+1\) subroutines \(\mathcal {V} = (\mathsf {ChS} _1, \ldots , \mathsf {ChS} _n, \mathsf {Vf})\) such that
  • \(\mathcal {P} _0(\mathsf {sk})\) computes the initial commitment \(\mathsf {com}\) sent as the first message.

  • \(\mathsf {ChS} _j, j \le n\) computes the j-th challenge message \(\mathsf {ch} _j\leftarrow _R\mathsf {C} _j\), sampling a random element from the j-th challenge space.

  • \(\mathcal {P} _i(\mathsf {sk}, \mathsf {trans} _{2i}), 0<i\le n\) computes the i-th response of the prover given access to the secret key and \(\mathsf {trans} _{2i}\), the transcript so far, containing the first 2i messages.

  • \(\mathsf {Vf} (\mathsf {pk}, \mathsf {trans})\), upon access to the public key and the whole transcript outputs \(\mathcal {V}\) ’s final decision.

The definition implies that a canonical \((2n+1)\)-pass IDS is public coin. The public coin property just says that the challenges are sampled from the respective challenge spaces using the uniform distribution.

El Yousfi et al. propose a generalized Fiat-Shamir transform that turns a canonical \((2n+1)\)-pass IDS into a digital signature scheme. The algorithms of the obtained signature scheme make use of the IDS algorithms as follows. The key generation is just the IDS key generation. The signature algorithm simulates an execution of the IDS, replacing challenge \(\mathsf {ch} _j\) by the output of a hash function (that maps into \(\mathsf {C} _j\)) that takes as input the concatenation of the message to be signed and all \(2(j-1)+1\) messages that have been exchanged so far. The signature just contains the messages sent by \(\mathcal {P}\). The verification algorithm uses the signature and the message to be signed to generate a full transcript, recomputing the challenges using the hash function. Then the verification algorithm runs \(\mathsf {Vf} \) on the public key and the computed transcript and outputs its result.

El Yousfi et al. give a reduction for the resulting signature scheme if the used IDS is honest-verifier zero-knowledge and fulfills special n-soundness defined below. The latter is a generalization of special soundness. Intuitively, special n-soundness says that given two transcripts that agree up to the second-to-last response but disagree on the last challenge, one can extract the secret key.

Definition 4.2

(Special n -soundness). A canonical \((2n+1)\)-pass IDS is said to fulfill special n-soundness if there exists a PPT algorithm \(\mathcal {E} \), called the extractor, that given two accepting transcripts \(\mathsf {trans} = (\mathsf {com},\) \(\mathsf {ch} _1,\) \(\mathsf {resp} _1,\) \(\ldots ,\) \(\mathsf {resp} _{n-1},\) \(\mathsf {ch} _n,\mathsf {resp} _n)\) and \(\mathsf {trans} ' = (\mathsf {com},\) \(\mathsf {ch} _1,\) \(\mathsf {resp} _1,\) \(\ldots ,\) \(\mathsf {resp} _{n-1},\) \(\mathsf {ch} _n',\mathsf {resp} _n')\) with \(\mathsf {ch} _n\ne \mathsf {ch} _n'\) as well as the corresponding public key \(\mathsf {pk}\), outputs a matching secret key \(\mathsf {sk}\) for \(\mathsf {pk}\) with non-negligible success probability.

The common special soundness for canonical (3-pass) IDS is hence just special 1-soundness. Please note that El Yousfi et al. define special n-soundness for the resulting signature scheme which in turn requires the used IDS to provide special n-soundness. We decided to follow the more common approach, defining the soundness properties for the IDS.

From \(\mathbf{(2}{\varvec{n}}{} \mathbf{+1)}\) to three passes. We now show that every canonical \((2n+1)\)-pass IDS that fulfills special n-soundness can be turned into a canonical 3-pass IDS fulfilling special soundness.

Theorem 4.3

Let \(\mathsf {IDS} = (\mathsf {KGen}, \mathcal {P}, \mathcal {V})\) be a canonical \((2n+1)\)-pass IDS that fulfills special n-soundness. Then, the following 3-pass IDS \(\mathsf {IDS} '=(\mathsf {KGen},\mathcal {P} ',\mathcal {V} ')\) is canonical and fulfills special soundness.

\(\mathsf {IDS} '\) is obtained from \(\mathsf {IDS}\) by just moving \(\mathsf {ChS} _j, 0< j < n\), (i.e. all but the last challenge generation algorithm) from \(\mathcal {V}\) to \(\mathcal {P}\): \(\mathcal {P} '\) computes \(\mathsf {com} ' = (\mathsf {com}, \mathsf {ch} _1, \mathsf {resp} _1, \ldots , \mathsf {resp} _{n-1}, \mathsf {ch} _{n-1})\) using \(\mathcal {P} _0, \ldots , \mathcal {P} _{n-1}\) and \(\mathsf {ChS} _1, \ldots , \mathsf {ChS} _{n-1}\). After \(\mathcal {P} '\) sent \(\mathsf {com} '\), \(\mathcal {V} '\) replies with \(\mathsf {ch} _1'\leftarrow \mathsf {ChS} _n(1^k)\). \(\mathcal {P} '\) computes \(\mathsf {resp} _1'\leftarrow \mathcal {P} _n(\mathsf {sk},\mathsf {trans} _{2n})\) and \(\mathcal {V} '\) verifies the transcript using \(\mathsf {Vf} \).


Clearly, \(\mathsf {IDS} '\) is a canonical 3-pass IDS. It remains to prove that it is honest-verifier zero-knowledge and that it fulfills special soundness. The latter is straight forward as two transcripts for \(\mathsf {IDS} '\), that fulfill the conditions in the soundness definition, can be turned into two transcripts for \(\mathsf {IDS} \) fulfilling the conditions in the n-soundness definition, splitting \(\mathsf {com} ' = (\mathsf {com},\) \(\mathsf {ch} _1,\) \(\mathsf {resp} _1,\) \(\ldots ,\) \(\mathsf {resp} _{n-1},\) \(\mathsf {ch} _{n-1})\) into its parts. Consequently, we can use any extractor for \(\mathsf {IDS}\) as an extractor for \(\mathsf {IDS} '\) running in the same time and having the exact same success probability.

Showing honest-verifier zero-knowledge is similarly straight forward. A simulator \(\mathcal {S} '\) for \(\mathsf {IDS} '\) can be obtained from any simulator \(\mathcal {S} \) for \(\mathsf {IDS} \). \(\mathcal {S} '\) just runs \(\mathcal {S} \) to obtain a transcript and regroups the messages to produce a valid transcript for \(\mathsf {IDS} '\). Again, \(\mathcal {S} '\) runs in essentially the same time as \(\mathcal {S} \) and achieves the exact same statistical distance.    \(\square \)

The Sakumoto et al. 5-pass IDS does not fulfill special n -soundness. The above result raises the question whether this property was overlooked and we can turn all the 5-pass schemes in the literature into 3-pass schemes. This would have the benefit that we could use the classical Fiat-Shamir transform to turn the resulting schemes into signature schemes.

Sadly, this is not the case. The reason is that the extractors for those IDS need more than two transcripts. For example, the extractor for the 5-pass IDS from [48] needs four transcripts such that they all agree on \(\mathsf {com} \). The transcripts have to form two pairs such that in a pair the transcripts agree on \(\mathsf {ch} _1\) but not on \(\mathsf {ch} _2\) and the two pairs disagree on \(\mathsf {ch} _1\). The proof given by El Yousfi et al. is flawed. The authors miss that the two secret shares \(\mathbf r _0\) and \(\mathbf r _1\) obtained from two different transcripts do not have to be shares of a valid secret key. We now give a formal proof.

Theorem 4.4

The 5-pass identification scheme from [48] does not fulfill special n-soundness if the computational \(\mathcal {MQ}\)-problem is hard.


We prove this by showing that there exist pairs of transcripts, fulfilling the special n-soundness criteria that can be generated by an adversary without knowledge of the secret key simulating just two executions of the protocol. As a key pair for the \(\mathcal {MQ}\)-IDS is a random instance of the \(\mathcal {MQ}\) problem, special n-soundness of the 5-pass \(\mathcal {MQ}\)-IDS would imply that the \(\mathcal {MQ}\) problem can be solved in probabilistic polynomial time.

Towards a contradiction, assume there exists a PPT extractor \(\mathcal {E}\) against the 5-pass \(\mathcal {MQ}\)-IDS that fulfills Definition 4.2. We show how to build a PPT solver \(\mathcal {A}\) for the \(\mathcal {MQ}\) problem. Given an instance of the \(\mathcal {MQ}\) problem \(\mathbf {v}\), \(\mathcal {A}\) sets \(\mathsf {pk} =\mathbf {v}\) which is a valid public key for the \(\mathcal {MQ}\)-IDS. Next, \(\mathcal {A}\) computes two transcripts as follows. \(\mathcal {A}\) samples a random \(\alpha \in \mathbb {F}_q\) and random \(\mathbf {s},\mathbf {r}_0,\mathbf {t}_0\in \mathbb {F}_q^n\), \(\mathbf {e}_0\in \mathbb {F}_q^m\), and computes \(\mathbf {r}_1\leftarrow \mathbf {s}-\mathbf {r}_0\), and \(\mathbf {t}_1\leftarrow \alpha \mathbf {r}_0-\mathbf {t}_0\). Then \(\mathcal {A}\) simulates two successful protocol executions, one for \(\mathsf {ch} _2=0\), one for \(\mathsf {ch} _2=1\). To do so, \(\mathcal {A}\) impersonates \(\mathcal {P} \) and replaces the first challenge with \(\alpha \) and the second with 0 in the first run and 1 in the second run. In addition, \(\mathcal {A}\) uses the knowledge of \(\alpha \) to compute the commitments as:
$$\begin{aligned} c_0\leftarrow Com(\mathbf {r}_0,\mathbf {t}_0,\mathbf {e}_0)\text {, and }c_1\leftarrow Com(\mathbf {r}_1,\alpha (\mathbf {v}-\mathbf F (\mathbf {r}_1))-\mathbf G (\mathbf {t}_1,\mathbf {r}_1)-\alpha \mathbf F (\mathbf {r}_0)+\mathbf {e}_0). \end{aligned}$$
Then \(\mathcal {A}\) computes \(\mathbf {e}_1\leftarrow \alpha \mathbf F (\mathbf {r}_0)-\mathbf {e}_0\) and sets the second commitment in both runs to \((\mathbf {t}_1,\mathbf {e}_1)\). For \(\mathsf {ch} _2=0\), \(\mathcal {A}\) sets \(\mathsf {resp} =\mathbf {r}_0\), and for \(\mathsf {ch} _2=1\), \(\mathcal {A}\) sets \(\mathsf {resp} =\mathbf {r}_1\).

Now, the first transcript (when \(\mathsf {ch} _2=0\)) is valid, since \(\mathbf {t}_0= \alpha \mathbf {r}_0-\mathbf {t}_1\) and \(\mathbf {e}_0= \alpha \mathbf F (\mathbf {r}_0)-\mathbf {e}_1\). The second transcript (when \(\mathsf {ch} _2=1\)) is also valid as a straight forward calculation shows. Finally, \(\mathcal {A}\) feeds the transcripts to \(\mathcal {E}\) and outputs whatever \(\mathcal {E}\) outputs. \(\mathcal {A}\) has the same success probability as \(\mathcal {E}\) and runs in essentially the same time. As \(\mathcal {E}\) is a PPT algorithm per assumption, this contradicts the hardness of the computational \(\mathcal {MQ}\) problem.    \(\square \)

Clearly, we can also use \(\mathcal {A}\) to deal with a parallel execution of many rounds of the scheme. A similar situation arises for all the 5-pass IDS schemes that we found in the literature.

4.2 A Fiat-Shamir Transform for Most \((2n+1)\)-pass IDS

By now we have established that we are currently lacking security arguments for signature schemes derived from \((2n+1)\)-pass IDS. We now show how to fix this issue for most \((2n+1)\)-pass IDS in the literature. As most of these IDS are 5-pass schemes that follow a certain structure, we restrict ourselves to these cases. There are some generalizations that are straight-forward and possible to deal with, but they massively complicate accessibility of our statements.

We will consider a particular type of 5-pass identification protocols where the length of the two challenges is restricted to q and 2.

Definition 4.5

( \(q2\text {-}\) Identification scheme). Let \(k\in \mathbb {N}\). A \(q2{{\mathrm{-}}}\)Identification scheme \(\mathsf {IDS} (1^k)\) is a canonical 5-pass identification scheme where for the challenge spaces \(\mathsf {C} _1\) and \(\mathsf {C} _2\) it holds that \(|\mathsf {C} _1|=q\) and \(|\mathsf {C} _2|=2\). Moreover, the probability that the commitment \(\mathsf {com}\) takes a given value is negligible (in k), where the probability is taken over the random choice of the input and the used randomness.

To keep the security reduction below somewhat generic, we also need a property that defines when an extractor exists for a q2-IDS. As we have seen special n-soundness is not applicable. Hence, we give a less generic definition.

Definition 4.6

( q2-Extractor). We say that a q2-Identification scheme \(\mathsf {IDS} (1^k)\) has a q2-extractor if there exists a PPT algorithm \(\mathcal {E} \), the extractor, that given a public key \(\mathsf {pk}\) and four transcripts \(\mathsf {trans} ^{(i)}=(\mathsf {com},\mathsf {ch} _{1}^{(i)}, \mathsf {resp} _{1}^{(i)}, \mathsf {ch} _{2}^{(i)},\mathsf {resp} _{2}^{(i)})\), \(i\in \{1,2,3,4\}\), with
$$\begin{aligned} \begin{array}{c} \mathsf {ch} ^{(1)}_{1}=\mathsf {ch} ^{(2)}_{1}\ne \mathsf {ch} ^{(3)}_{1}=\mathsf {ch} ^{(4)}_{1}, \mathsf {ch} ^{(1)}_{2}=\mathsf {ch} ^{(3)}_{2}\ne \mathsf {ch} ^{(2)}_{2}=\mathsf {ch} ^{(4)}_{2}, \end{array} \end{aligned}$$
valid with respect to \(\mathsf {pk}\), outputs a matching secret key \(\mathsf {sk} \) for \(\mathsf {pk} \) with non-negligible success probability (in k).

In what follows, let \(\mathsf {IDS} ^r = (\mathsf {KGen},\mathcal {P} ^r,\mathcal {V} ^r)\) be the parallel composition of r rounds of the identification scheme \(\mathsf {IDS} = (\mathsf {KGen},\mathcal {P},\mathcal {V})\). As the schemes we are concerned with only achieve a constant soundness error, the construction below uses a polynomial number of rounds to obtain an IDS with negligible soundness error as intermediate step. We denote the transcript of the j-th round by \(\mathsf {trans} _j=(\mathsf {com} _j,\mathsf {ch} _{1,j}, \mathsf {resp} _{1,j},\mathsf {ch} _{2,j},\mathsf {resp} _{2,j})\).

Construction 4.7

(Fiat-Shamir transform for q2-IDS). Let \(k\in \mathbb {N}\) the security parameter, \(\mathsf {IDS} = (\mathsf {KGen},\mathcal {P},\mathcal {V})\) a q2-Identification scheme that achieves soundness with soundness error \(\kappa \). Select r, the number of (parallel) rounds of \(\mathsf {IDS}\), such that \(\kappa ^r = \text {negl}{(k)}\), and that the challenge spaces of the composition \(\mathsf {IDS} ^r\), \(\mathsf {C} _1^r, \mathsf {C} _2^r\) have exponential size in k. Moreover, select cryptographic hash functions \(H_1:\{0,1\}^*\rightarrow \mathsf {C} _1^r\) and \(H_2:\{0,1\}^*\rightarrow \mathsf {C} _2^r\). The q2-signature scheme q2-\(\mathsf {\textsf {Dss}}(1^k)\) derived from \(\mathsf {IDS}\) is the triplet of algorithms \((\mathsf {KGen,Sign,Vf})\) with:
  • \((\mathsf {sk},\mathsf {pk})\leftarrow \mathsf {KGen} (1^k)\),

  • \(\sigma =(\sigma _0,\sigma _1,\sigma _2)\leftarrow \mathsf {Sign} (\mathsf {sk}, m)\) where \(\sigma _0=\mathsf {com} \leftarrow \mathcal {P} ^r_0(\mathsf {sk})\), \(h_1=H_1(m,\sigma _0)\), \(\sigma _1=\mathsf {resp} _{1}\leftarrow \mathcal {P} ^r_1(\mathsf {sk},\sigma _0,h_{1})\), \(h_2=H_2(m,\sigma _0,h_1,\sigma _1)\), and \(\sigma _2=\mathsf {resp} _{2}\leftarrow \mathcal {P} ^r_2(\mathsf {sk},\sigma _0,h_1,\sigma _1,h_{2})\).

  • \(\mathsf {Vf}(\mathsf {pk},m, \sigma )\) parses \(\sigma =(\sigma _0,\sigma _1,\sigma _2)\), computes the values \(h_1= H_1(m,\sigma _0)\), \(h_2= H_2(m,\sigma _0,h_1,\sigma _1)\) as above and outputs \(\mathcal {V} ^r(\mathsf {pk},\sigma _0,h_1,\sigma _1,h_2,\sigma _2)\).

Correctness of the scheme follows immediately from the correctness of \(\mathsf {IDS}\).

4.3 Security of q2-signature Schemes

We now give a security reduction for the above transform in the random oracle model assuming that the underlying q2-IDS is honest-verifier zero-knowledge, achieves soundness with constant soundness error, and has a q2-extractor. More specifically, we prove the following theorem:

Theorem 4.8

(EU-CMA security of q2-signature schemes). Let \(k\in \mathbb {N}\), \(\mathsf {IDS} (1^k)\) a q2-IDS that is honest-verifier zero-knowledge, achieves soundness with constant soundness error \(\kappa \) and has a q2-extractor. Then \(q2{{\mathrm{-}}}\mathsf {\textsf {Dss}}(1^k)\), the q2-signature scheme derived applying Construction 4.7 is existentially unforgeable under adaptive chosen message attacks.

In the following, we model the functions \(H_1\) and \(H_2\) as independent random oracles \(\mathcal {O}_1\) and \(\mathcal {O}_2\). To proof Theorem 4.8, we proceed in several steps. Our proof builds on techniques introduced by Pointcheval and Stern [47]. As the reduction is far from being tight, we refrain from doing an exact proof as it does not buy us anything but a complicated statement. We first recall an important tool from [47] called the splitting lemma.

Lemma 4.9

(Splitting lemma [47]). Let \(A\subset X\times Y\), such that

\({\text {Pr}}[A(x,y)] \geqslant \epsilon \). Then, there exists \(\varOmega \subset X\), such that
$$\begin{aligned} {\text {Pr}}[x\in \varOmega ]\geqslant \epsilon /2,\text { and } {\text {Pr}}[A(a,y)|a\in \varOmega ]\geqslant \epsilon /2. \end{aligned}$$

We now present a forking lemma for q2-signature schemes. The lemma shows that we can obtain four valid signatures which contain four valid transcripts of the underlying IDS, given a successful key-only adversary. Moreover, these four traces fulfill a certain requirement on the challenges (here the related parts of the hash function outputs) that we need later.

Lemma 4.10

(Forking lemma for q2-signature schemes). Let \(k\in \mathbb {N}\), \(\mathsf {\textsf {Dss}}(1^k)\) a q2-signature scheme with security parameter k. If there exists a PPT adversary \(\mathcal {A}\) that can output a valid signature message pair \((m,\sigma )\) with non-negligible success probability, given only the public key as input, then, with non-negligible probability, rewinding \(\mathcal {A}\) a polynomial number of times (with same randomness) but different oracles, outputs 4 valid signature message pairs \((m,\sigma =(\sigma _0,\sigma ^{(i)}_1,\sigma ^{(i)}_2)\), \(i\in \{1,2,3,4\}\), such that for the associated hash values it holds that
$$\begin{aligned} \begin{array}{c} h^{(1)}_{1,j}=h^{(2)}_{1,j}\ne h^{(3)}_{1,j}=h^{(4)}_{1,j}, h^{(1)}_{2,j}=h^{(3)}_{2,j}\ne h^{(2)}_{2,j}=h^{(4)}_{2,j}, \end{array} \end{aligned}$$
for some round \(j\in \{1,\dots ,r\}\).


To prove the Lemma we need to show that we can rewind \(\mathcal {A}\) three times and the probability that \(\mathcal {A}\) succeeds in forging a (different) signature in all four runs is non-negligible. Moreover, we have to show that the signatures have the additional property claimed in the Lemma, again with non-negligible probability.

Let \(\omega \in R_w\) be \(\mathcal {A}\) ’s random tape with \(R_w\) the set of allowable random tapes. During the attack \(\mathcal {A}\) may ask polynomially many queries (in the security parameter k) \(Q_1(k)\) and \(Q_2(k)\) to the random oracles \(\mathcal {O}_1\) and \(\mathcal {O}_2\). Let \(q_{1,1},\) \(q_{1,2}, \dots ,\) \(q_{1,Q_1}\) and \(q_{2,1},\) \(q_{2,2}, \dots ,\) \(q_{2,Q_2}\) be the queries to \(\mathcal {O}_1\) and \(\mathcal {O}_2\), respectively. Moreover, let \((r_{1,1},r_{1,2},\dots ,r_{1,Q_1})\in (\mathsf {C} _1^r)^{Q_1}\) and \((r_{2,1},r_{2,2},\dots ,r_{2,Q_2})\in (\mathsf {C} _2^r)^{Q_2}\) the corresponding answers of the oracles.

Towards proving the first point, we assume that \(\mathcal {A}\) also outputs \(h_1,h_2\) with the signature and a signature is considered invalid if those do not match the responses of \(\mathcal {O}_1\) and \(\mathcal {O}_2\), respectively. This assumption is without loss of generality as we can construct such \(\mathcal {A}\) from any \(\mathcal {A} '\) that does not output \(h_1,h_2\). \(\mathcal {A}\) just runs \(\mathcal {A} '\) and given the result queries \(\mathcal {O}_1\) and \(\mathcal {O}_2\) for \(h_1,h_2\) and outputs everything. Clearly \(\mathcal {A}\) succeeds with the same success probability as \(\mathcal {A} '\) and runs in essentially the same time, making just one more query to each RO.

Denote by \(\mathsf {F}\) the event that \(\mathcal {A}\) outputs a valid message signature pair \((m,\sigma ^{(1)}=(\sigma _0,\sigma ^{(1)}_1,\sigma ^{(1)}_2))\) with the associated hash values \(h_1^{(1)},h_2^{(1)}\). Per assumption, this event occurs with non-negligible probability, i.e., \(\mathsf {Pr}[\mathsf {F}]=\frac{1}{P(k)},\) for some polynomial P(k). In addition, \(\mathsf {F}\) implies \(h^{(1)}_1=\mathcal {O}_1(m,\sigma _0)\) and \(h^{(1)}_2=\mathcal {O}_2(m,\sigma _0,h^{(1)}_1,\sigma ^{(1)}_1)\). As \(h^{(1)}_1,h_2^{(1)}\) are chosen uniformly at random from exponentially large sets \(\mathsf {C} _1^r,\mathsf {C} _2^r\), the probability that \(\mathcal {A}\) did not query \(\mathcal {O} _1\) for \(h^{(1)}_1\) and \(\mathcal {O} _2\) for \(h^{(1)}_2\) is negligible. Hence, there exists a polynomial \(P'\) such that the event \(\mathsf {F}'\) that \(\mathsf {F}\) occurs and \(\mathcal {A}\) queried \(\mathcal {O} _1\) for \(h^{(1)}_1\) and \(\mathcal {O} _2\) for \(h^{(1)}_2\) has probability \(\displaystyle \mathsf {Pr}[\mathsf {F}']=\frac{1}{P'(k)}.\)

For the moment only consider the second oracle. As of the previous equation, there exists at least one \(\beta \leqslant Q_2\) such that
$$\begin{aligned} \mathsf {Pr}[\mathsf {F}' \wedge q_{2,\beta }=(m,\sigma _0,h^{(1)}_1,\sigma ^{(1)}_1)]\geqslant \frac{1}{Q_2(k)P'(k)} \end{aligned}$$
where the probability is taken over the random coins of \(\mathcal {A}\) and \(\mathcal {O}_2\). Informally, the following steps just show that the success of an algorithm with non-negligible success probability cannot be conditioned on an event that occurs only with negligible probability (i.e. the outcome of the \(q_{2,\beta }\) query landing in some negligible subset).
Let \(\mathcal {B}=\{(\omega ,r_{2,1},r_{2,2},\dots ,r_{2,Q_2})|\omega \in R_w\wedge (r_{2,1},r_{2,2},\dots ,r_{2,Q_2})\in (\mathsf {C} _2^r)^{Q_2}\wedge \mathsf {F}'\wedge q_{2,\beta }=(m,\sigma _0,h^{(1)}_1,\sigma ^{(1)}_1)\}\), i.e., the set of random tapes and oracle responses such that \(\mathsf {F}'\wedge q_{2,\beta }=(m,\sigma _0,h^{(1)}_1,\sigma ^{(1)}_1)\). This implies that there exists a non-negligible set of “good” random tapes \(\varOmega _{\beta }\subseteq R_{\omega }\) for which \(\mathcal {A}\) can provide a valid signature and \(q_{2,\beta }\) is the oracle query fixing \(h^{(1)}_2\). Applying the splitting lemma, we get that
$$\begin{aligned} {\text {Pr}}[w\in \varOmega _{\beta }]\geqslant \frac{1}{2 Q_2(k)P'(k)}\\ {\text {Pr}}[(\omega ,r_{2,1},r_{2,2},\dots ,r_{2,Q_2})\in \mathcal {B}|w\in \varOmega _{\beta }]\geqslant \frac{1}{2 Q_2(k)P'(k)} \end{aligned}$$
Applying the same reasoning again we can derive from the later probability being non-negligible that there exists a non-negligible subset \(\varOmega _{\beta ,\omega }\) of the “good” oracle responses \((r_{2,1},r_{2,2},\dots ,r_{2,\beta -1})\) such that \((\omega ,r_{2,1},r_{2,2},\dots ,r_{2,Q_2})\in \mathcal {B}\). Applying the splitting lemma again, we get
$$\begin{aligned} {\text {Pr}}[(r_{2,1},\dots ,r_{2,\beta -1})\in \varOmega _{\beta ,\omega }]\geqslant \frac{1}{4 Q_2(k)P'(k)}\\ {\text {Pr}}[(\omega ,r_{2,1},\dots ,r_{2,Q_2})\in \mathcal {B}|(r_{2,1},\dots ,r_{2,\beta -1})\in \varOmega _{\beta ,\omega })]\geqslant \frac{1}{4 Q_2(k)P'(k)} \end{aligned}$$
This means that rewinding \(\mathcal {A}\) to the point where it made query \(q_{2,\beta }\) and running it with new, random \(r_{2,\beta }',\dots ,r_{2,Q_2}'\) has a non-negligible probability of \(\mathcal {A}\) outputting another valid signature. Therefore, we can use \(\mathcal {A}\) to find two valid signature message pairs with associated hash values \((m, \sigma =(\sigma _0,\sigma ^{(1)}_1,\sigma ^{(1)}_2),h^{(1)}_1, h^{(1)}_2)\), \((m, \sigma ^{(2)}=(\sigma _0,\sigma ^{(2)}_1,\sigma ^{(2)}_2),\) \(h^{(2)}_1, h^{(2)}_2)\), with \(h^{(1)}_2 \ne h^{(2)}_2\) and such that \((\sigma _0,h^{(1)}_1,\sigma ^{(1)}_1)=(\sigma _0,h^{(2)}_1,\sigma ^{(2)}_1)\), with non-negligible probability.

We now rewind the adversary again using exactly the same technique as above but now considering the queries to \(\mathcal {O}_1\) and its responses. In the replay we change the responses of \(\mathcal {O}_1\) to obtain a third signature that differs from the previously obtained ones in the first associated hash value. It can be shown that with non-negligible probability \(\mathcal {A}\) will output a third signature on m, \(\sigma ^{(3)}=(\sigma _0,\sigma ^{(3)}_1,\sigma ^{(3)}_2)\), with associated hash values \((h^{(3)}_1,h^{(3)}_2)\) such that \(h^{(3)}_1\ne h^{(2)}_1=h^{(1)}_1\).

Finally, we rewind the adversary a third time, keeping the responses of \(\mathcal {O} _1\) from the last rewind and focusing on \(\mathcal {O} _2\) again. Again, with non-negligible probability \(\mathcal {A}\) will produce yet another signature on m, \(\sigma ^{(4)}=(\sigma _0,\sigma ^{(4)}_1,\sigma ^{(4)}_2)\) with associated hash values \((h^{(4)}_1,h^{(4)}_2)\) such that \(h^{(4)}_1=h^{(3)}_1\) and \(h^{(4)}_2\ne h^{(3)}_2\).

Summing up, rewinding the adversary three times, we can find four valid signatures \(\sigma ^{(1)}, \sigma ^{(2)}, \sigma ^{(3)}, \sigma ^{(4)}\) with the above property on the associated hash values with non-negligible success probability \(\displaystyle \frac{1}{P(k)}\) for some polynomial P(k). Let us denote this event by \(\mathcal {E}_\sigma \). So we have that \(\displaystyle {\text {Pr}}[\mathcal {E}_\sigma ]\geqslant \frac{1}{P(k)}.\)

What remains is to show that the obtained signatures satisfy the particular structure from the lemma (Eq. 4) with non-negligible probability.

Let \(\mathcal {H}\) be the event that there exists a \(j\in \{1,\dots ,r\}\) such that (4) is satisfied. We have that
$$\begin{aligned} \mathsf {Pr}[\mathcal {E}_\sigma \!\wedge \!\mathcal {H}]=\mathsf {Pr}[\mathcal {E}_\sigma ]\!-\!\mathsf {Pr}[\lnot \mathcal {H}\!\wedge \!\mathcal {E}_\sigma ]\!=\! \mathsf {Pr}[\mathcal {E}_\sigma ]\!-\!\mathsf {Pr}[\lnot \mathcal {H}|\mathcal {E}_\sigma ]\mathsf {Pr}[\mathcal {E}_\sigma ] \geqslant \frac{1}{P(k)}\!-\!\mathsf {Pr}[\lnot \mathcal {H}|\mathcal {E}_\sigma ] \end{aligned}$$
We will now give a statistical argument why \(\mathsf {Pr}[\lnot \mathcal {H}|\mathcal {E}_\sigma ]\) is negligible.
As argued above, the hash values associated with the signatures must be outcomes of the RO queries of \(\mathcal {A}\). During its first run, \(\mathcal {A}\) can choose the first hash value \(h_1^{(1)}\) from his \(Q_1\) queries to \(\mathcal {O} _1\) and the second hash value \(h_2^{(1)}\) from his \(Q_2\) queries to \(\mathcal {O} _2\). The total number of possible combinations is \(Q_1Q_2\). The hash values associated with the second signature are \(h_1^{(2)} = h_1^{(1)}\) (as \(\mathcal {E}_\sigma \)) and \(h_2^{(2)}\). So, the first hash value is fixed and the second is chosen from a set of no more than \(Q_2\) responses from \(\mathcal {O} _2\). Following the same arguments, the hash pair associated with the third signature is chosen from a set of size \(Q_1Q_2\) and the one associated with the fourth signature from a set of size \(Q_2\). The oracle outputs are uniformly distributed within \(\mathsf {C} _1^r\) and \(\mathsf {C} _2^r\), respectively. Hence, the set of all possible combinations of hash values that \(\mathcal {A}\) could output has size
$$\begin{aligned} \lambda (k) \le Q_1Q_2 \cdot Q_2 \cdot Q_1Q_2 \cdot Q_2, \end{aligned}$$
which is a polynomial in k as \(Q_1\) and \(Q_2\) are.
Recall \(\mathsf {C} _1\) has size q and \(\mathsf {C} _2\) size 2. The probability that the required pattern did not occur in the four-tupel of challenges derived from random hash values for one internal round j is
$$\begin{aligned} \mathsf {Pr}[\lnot \mathcal {H}_j]=1-\mathsf {Pr}[\mathcal {H}_j]=1-\frac{q-1}{2^2q} = \frac{3q+1}{4q}. \end{aligned}$$
The last follows from the fact that out of all \(2^4q^2\) 4-tuples \(((\alpha _1,\beta _1),(\alpha _1,\beta _2),\) \((\alpha _2,\beta _3),(\alpha _2,\beta _4))\in (\mathsf {C} _1\times \mathsf {C} _2)^4\) exactly \(2^2q(q-1)\) satisfy \(\alpha _1\ne \alpha _2\), \(\beta _1\ne \beta _2\), \(\beta _3\ne \beta _4\). Hence, the probability that a random four-tuple of hash values does not have a single internal round that satisfies (4) and hence fulfills \(\lnot \mathcal {H}\) is
$$\begin{aligned} \mathsf {Pr}[\lnot \mathcal {H}]= \left( \frac{3q+1}{4q}\right) ^r = \text {negl}{(k)}. \end{aligned}$$
According to Construction 4.7, the number of rounds r must be super-logarithmic (in k), to fulfill \(\mathsf {C} _2^r\) being exponentially large (in k). Hence, the above is negligible for random hash values.

Finally, we just have to combine the two results. The adversary can at most choose out of a polynomially bounded number of four-tuples of hash pairs. Each of these four-tuples has a negligible probability of fulfilling \(\lnot \mathcal {H}\). Hence, the probability that all the possible combinations of query responses even contain a four-tuple that does not fulfill \(\mathcal {H}\) is negligible. So, \(\mathsf {Pr}[\lnot \mathcal {H}|\mathcal {E}_\sigma ] = \text {negl}{(k)},\) and hence, the conditions from the lemma are satisfied with non-negligible probability.    \(\square \)

With Lemma 4.10 we can already establish unforgeability under key only attacks:

Corollary 4.11

(Key-only attack resistance). Let \(k\in \mathbb {N}\), \(\mathsf {IDS} (1^k)\) a q2-IDS that achieves soundness with constant soundness error \(\kappa \) and has a q2-extractor. Then \(q2{{\mathrm{-}}}\mathsf {\textsf {Dss}}(1^k)\), the q2-signature scheme derived applying Construction 4.7 is unforgeable under key-only attacks.

A straight forward application of Lemma 4.10 allows to generate the four traces needed to apply the q2-extractor. The obtained secret key can then be used to violate soundness.

For \(\mathsf {\textsf {{EU\text {-}CMA}}}\) security, we still have to deal with signature queries. The following lemma shows that a reduction can produce valid responses to the adversarial signature queries if the identification scheme is honest-verifier zero-knowledge.

Lemma 4.12

Let \(k\in \mathbb {N}\) the security parameter, \(\mathsf {IDS} (1^k)\) a q2-IDS that is honest-verifier zero-knowledge. Then any PPT adversary \(\mathcal {B}\) against the \(\mathsf {\textsf {{EU\text {-}CMA}}}\)-security of \(q2{{\mathrm{-}}}\mathsf {\textsf {Dss}}(1^k)\), the q2-signature scheme derived by applying Construction 4.7, can be turned into a key-only adversary \(\mathcal {A} \) with the properties described in Lemma 4.10. \(\mathcal {A}\) runs in polynomial time and succeeds with essentially the same success probability as \(\mathcal {B}\).


By construction. We show how to construct an oracle machine \(\mathcal {A} ^{\mathcal {B},\mathcal {S},\mathcal {O} _1,\mathcal {O} _2}\) that has access to \(\mathcal {B}\), an honest-verifier zero-knowledge simulator \(\mathcal {S}\), and random oracles \(\mathcal {O} _1, \mathcal {O} _2\). \(\mathcal {A}\) produces a valid signature for \(q2{{\mathrm{-}}}\mathsf {\textsf {Dss}}(1^k)\) given only a public key running in time polynomial in k and achieving essentially the same success probability (up to a negligible difference) as \(\mathcal {B}\).

Upon input of public key \(\mathsf {pk}\), \(\mathcal {A}\) runs \(\mathcal {B} ^{\mathcal {O} _1', \mathcal {O} _2',\mathsf {Sign}}(\mathsf {pk})\) simulating the random oracles (ROs) \(\mathcal {O} _1', \mathcal {O} _2'\), as well as the signing oracle \(\mathsf {Sign}\) towards \(\mathcal {B}\). When \(\mathcal {B}\) outputs a forgery \((m^*,\sigma ^*)\), \(\mathcal {A}\) just forwards it.

To simulate the ROs, \(\mathcal {A}\) keeps two initially empty tables of query-response pairs, one per oracle. Whenever \(\mathcal {B}\) queries \(\mathcal {O} _b'\), \(\mathcal {A}\) first checks if the table for \(\mathcal {O} _b'\) already contains a pair for this query. If such a pair exists, \(\mathcal {A}\) just returns the stored response. Otherwise, \(\mathcal {A}\) forwards the query to its own \(\mathcal {O} _b\).

As \(\mathsf {IDS}\) is honest-verifier zero-knowledge there exists a PPT simulator \(\mathcal {S}\) that upon input of a \(\mathsf {IDS}\) public key generates a valid transcript that is indistinguishable of the transcripts generated by honest protocol executions. Whenever \(\mathcal {B}\) queries the signature oracle with message m, \(\mathcal {A}\) runs \(\mathcal {S}\) r times, to obtain r valid transcripts. \(\mathcal {A}\) combines the transcripts to obtain a valid signature with associated hashes \(\sigma =((\sigma _0,\sigma _1,\sigma _2), h_1, h_2)\). Before outputting \(\sigma \), \(\mathcal {A}\) checks if the table for \(\mathcal {O} _1'\) already contains an entry for query \((m,\sigma _0)\). If so, \(\mathcal {A}\) aborts. Otherwise, \(\mathcal {A}\) adds the pair \(((m,\sigma _0), h_1)\). Then, \(\mathcal {A}\) checks the second table for query \((m,\sigma _0,h_1,\sigma _1)\). Again, \(\mathcal {A}\) aborts if it finds such an entry and adds \(((m,\sigma _0,h_1,\sigma _1), h_2)\), otherwise.

The probability that \(\mathcal {A}\) aborts is negligible in k. When answering signature queries, \(\mathcal {A}\) verifies that certain queries were not made before. Both queries contain \(\sigma _1\) which takes any given value only with negligible probability. On the other hand, the total number of queries that \(\mathcal {B}\) makes to all its oracles is polynomially bounded. Hence, the probability that one of the two queries was already made before is negligible. If \(\mathcal {A}\) does not abort, it perfectly simulates all oracles towards \(\mathcal {B}\). Hence, \(\mathcal {B}\) – and thereby \(\mathcal {A}\) – succeeds with the same probability as in the real \(\mathsf {\textsf {{EU\text {-}CMA}}}\) game in this case. Hence, \(\mathcal {A}\) succeeds with essentially the same probability as \(\mathcal {B}\).    \(\square \)

We now got everything we need to prove Theorem 4.8. The proof is a straight forward application of the previous two lemmas.


(of Theorem 4.8 ). Towards a contradiction, assume that there exists a PPT adversary \(\mathcal {B}\) against the \(\mathsf {\textsf {{EU\text {-}CMA}}}\)-security of \(q2{{\mathrm{-}}}\mathsf {\textsf {Dss}}\) succeeding with non-negligible probability. We show how to construct a PPT impersonator \(\mathcal {C}\) breaking the soundness of \(\mathsf {IDS}\). Applying Lemma 4.12, \(\mathcal {C}\) can construct a PPT key-only forger \(\mathcal {A}\), with essentially the same success probability as \(\mathcal {B}\). Given a public key for \(\mathsf {IDS}\) (which is a valid \(q2\text {-}\mathsf {\textsf {Dss}}\) public key) \(\mathcal {C}\) runs \(\mathcal {A}\) as described in Lemma 4.10. That way \(\mathcal {C}\) can use \(\mathcal {A}\) to obtain four signatures that per (4) lead four transcripts as required by the q2-extractor \(\mathcal {E}\). Running \(\mathcal {E}\), \(\mathcal {C}\) can extract a valid secret key that allows to impersonate \(\mathcal {P}\) with success probability 1.

\(\mathcal {C}\) just runs \(\mathcal {A}\) and \(\mathcal {E}\), two PPT algorithms. Consequently, \(\mathcal {C}\) runs in polynomial time. Also, \(\mathcal {A}\) and \(\mathcal {E}\) both have non-negligible success probability implying that also \(\mathcal {C}\) succeeds with non-negligible probability.    \(\square \)

5 Our Proposal

In the previous sections, we gave security arguments for a Fiat-Shamir transform of 5-pass IDS that contain two challenges, from \(\{0, \dots , q-1\}\) and \(\{0, 1\}\) respectively, where \(q\in \mathbb {Z}^*\). In this section we apply the transform to the 5-pass IDS from [48] (see Sect. 3). Before discussing the 5-pass scheme, which we dub MQDSS, we first briefly examine the signature scheme obtained by applying the traditional Fiat-Shamir transform to the 3-pass IDS in [48], to obtain a baseline. Then we give a generic description of MQDSS and prove it secure.

The IDS requires an \(\mathcal {MQ}\) system \(\mathbf F \) as input, potentially system-wide. We could simply select one function \(\mathbf F \) and define it as a system parameter for all users. Instead, we choose to derive it from a unique seed that is included in each public key. This increases the size of \(\mathsf {pk}\) by k bits, and adds some cost for seed expansion when signing and verifying. However, selecting a single system-wide \(\mathbf F \) might allow an attacker to focus their efforts on a single \(\mathbf F \) for all users, and would require whoever selects this system parameter to convince all users of its randomness (which is not trivial [5]). For consistency with literature, we still occasionally refer to \(\mathbf F \) as the ‘system parameter’.

Note that the signing procedure described below is slightly more involved than is suggested by Construction 4.7. Where the transformed construction operates directly on the message m, we first apply what is effectively a randomized hash function. As discussed in [35], this extra step provides resilience against collisions in the hash function at only little extra cost. A similar construction appears e.g. in SPHINCS [6]. The digest (and thus the signature) is still derived from m and \(\mathsf {sk}\) deterministically.

5.1 Establishing a Baseline Using the 3-Pass Scheme over \(\mathbb {F}_2\)

In the interest of brevity, we will not go into the details of the derived signature scheme here – instead, we refer to the full version of the paper [13].

For the 3-pass scheme, we select \(n = m = 256\) over \(\mathbb {F}_2\). This results in signatures of 54.81 KB, and a key pair of 64 bytes per key. We ran benchmarks on a single 3.5 GHz core of an Intel Core i7-4770K CPU, measuring 118 088 992 cycles for signature generation, 8 066 324 cycles for key generation and 82 650 156 cycles for signature verification (or 33.7 ms, 2.30 ms and 23.6 ms, respectively).

5.2 The 5-Pass Scheme over \(\mathbb {F}_{31}\)

As can be seen from the results above, the plain 3-pass scheme over \(\mathbb {F}_{2}\) is quite inefficient, both in terms of signature size and signing speed. This is a direct consequence of the large number of variables and equations required to achieve 128 bits of post-quantum security using \(\mathcal {MQ}\) over \(\mathbb {F}_{2}\), as well as the high number of rounds required (see the full version [13] of the paper for an analysis). Using a 5-pass scheme over \(\mathbb {F}_{31}\) allows for a smaller n and m, as well as a smaller number of rounds. One might wonder why we do not consider different fields for the 3-pass scenario, instead. This turns out to be suboptimal: contrary to the 5-pass scheme, this does not result in a knowledge error reduction, but does increase the transcript size per round.

The MQDSS signature scheme. We now explicitly construct the functions \(\mathsf {KGen} \), \(\mathsf {Sign} \) and \(\mathsf {Vf} \) in accordance with Definition 2.1. Specific values for the parameters that achieve 128 bit post-quantum security are given in the next section. We start by presenting the parameters of the scheme in general.

Parameters. MQDSS is parameterized by a security parameter \(k\in \mathbb {N}\), and \(m,n \in \mathbb {N}\) such that the security level of the \(\mathcal {MQ}\) instance \(\mathcal {MQ} (n, m, \mathbb {F}_2) \ge k\). The latter fix the description length of the equation system \(\mathbf F \), \(F_{len} = m \cdot \frac{n \cdot (n + 1)}{2}\).

  • Cryptographic hash functions \(\mathcal {H}: \{0, 1\}^* \rightarrow \{0, 1\}^k\), \(H_1: \{0, 1\}^{2k} \rightarrow {\mathbb {F}_{31}}^r\), and \(H_2: \{0, 1\}^{2k} \rightarrow \{0,1\}^r\).

  • two string commitment functions \(Com_0: {\mathbb {F}_{31}}^n \times {\mathbb {F}_{31}}^n \times {\mathbb {F}_{31}}^m \rightarrow \{0, 1\}^k\) and \(Com_1: {\mathbb {F}_{31}}^n \times {\mathbb {F}_{31}}^m \rightarrow \{0, 1\}^k\),

  • pseudo-random generators \(G_{\mathcal {S}_F}: \{0, 1\}^k \rightarrow {\mathbb {F}_{31}}^{F_{len}}\), \(G_{SK}: \{0, 1\}^k \rightarrow {\mathbb {F}_{31}}^{n}\), and \(G_c: \{0, 1\}^{2k} \rightarrow {\mathbb {F}_{31}}^{r \cdot (2n + m)}\).

Key generation. Given the security parameter k, we randomly sample a secret key of k bits \(SK \leftarrow _R\{0, 1\}^k\) as well as a seed \(\mathcal {S}_F \leftarrow _R\{0, 1\}^k\). We then select a pseudorandom \(\mathcal {MQ}\) system \(\mathbf F \) from \(\mathcal {MQ} (n, m, \mathbb {F}_{31})\) by expanding \(\mathcal {S}_F\). In total, we must generate \(F_{len} = m \cdot (\frac{n \cdot (n + 1)}{2} + n)\) elements for \(\mathbf F \), to use as coefficients for both the quadratic and the linear monomials. We use the pseudorandom generator \(G_{\mathcal {S}_F}\) for this.

In order to compute the public key, we want to use the secret key as input for the \(\mathcal {MQ}\) function defined by \(\mathbf F \). As SK is a k-bit string rather than a sequence of n elements from \(\mathbb {F}_{31}\), we instead use it as a seed for a pseudorandom generator as well, deriving \(SK_{\mathbb {F}_{31}} = G_{SK}(SK)\). It is then possible to compute \({{\varvec{PK}}}_{{\varvec{v}}} = \mathbf F (SK_{\mathbb {F}_{31}})\). The secret key \(\mathsf {sk} = (SK, \mathcal {S}_F)\) and the public key \(\mathsf {pk} = (\mathcal {S}_F, {{\varvec{PK}}}_{{\varvec{v}}})\) require \(2 \cdot k\) and \(k + 5 \cdot m\) bits respectively, assuming 5 bits per \(\mathbb {F}_{31}\) element.

Signing. The signature algorithm takes as input a message \(m \in \{0, 1\}^*\) and a secret key \(\mathsf {sk} = (SK, \mathcal {S}_F)\). Similarly as in the key generation, we derive \(\mathbf F = G_{\mathcal {S}_F}(\mathcal {S}_F)\). Then, we derive a message-dependent random value \(R = \mathcal {H}(SK\) \(\Vert \) m), where “\(\Vert \)” is string concatenation. Using this random value R, we compute the randomized message digest \(D = \mathcal {H}(R\) \(\Vert \) m). The value R must be included in the signature, so that a verifier can derive the same randomized digest.

As mentioned in Definition 2.4, the core of the derived signature scheme essentially consists of iterations of the IDS. We refer to the number of required iterations to achieve the security level k as r (note that this should not be confused with \(\mathbf r _0\) and \(\mathbf r _1\), which are vectors of elements of \(\mathbb {F}_{31}\)).

Given SK and D, we now compute \(G_c(SK, D)\) to produce \((\mathbf r _{(0, 0)},\) \(\ldots ,\) \(\mathbf r _{(0, r)},\) \(\mathbf t _{(0, 0)},\) \(\ldots ,\) \(\mathbf t _{(0, r)},\) \(\mathbf e _{(0, 0)},\) \(\ldots ,\) \(\mathbf e _{(0, r)})\). Using these values, we compute \(c_{(0, i)}\) and \(c_{(1, i)}\) for each round i, as defined in the IDS. Recall that \(\mathbf G (\mathbf {x},\mathbf {y})=\mathbf F (\mathbf {x}+\mathbf {y})-\mathbf F (\mathbf {x})-\mathbf F (\mathbf {y})\), and that \(Com_0\) and \(Com_1\) are string commitment functions:
$$\begin{aligned} \begin{array}{rl} c_{(0, i)}\! =\! Com_0(\mathbf r _{(0,i)},\mathbf t _{(0,i)},\mathbf e _{(0,i)}) {\ \mathrm and\ } c_{(1, i)}\! =\! Com_1(\mathbf r _{(1,i)},\mathbf G (\mathbf t _{(0,i)},\mathbf r _{(1,i)})+\! \mathbf e _{(0, i)}). \\ \end{array} \end{aligned}$$
As mentioned in [48], it is not necessary to include all 2r commitments in the transcript. Instead, we include a digest over the concatenation of all commitments \(\sigma _0 = \mathcal {H}(c_{(0, 0)} \Vert c_{(1, 0)} \Vert \ldots \Vert c_{(0, r - 1)} \Vert c_{(1, r - 1)})\). We derive the challenges2 \(\alpha _i \in \mathbb {F}_{31}\) (for \(0 \le i < r\)) by applying \(H_1\) to \(h_1 = (D, \sigma _0)\). Using these \(\alpha _i\), the vectors \(\mathbf t _{(1, i)} = \alpha _i \cdot \mathbf r _{(0, i)} - \mathbf t _{(0, i)}\) and \(\mathbf e _{(1, i)} = \alpha _i \cdot \mathbf {F}(\mathbf r _{(0, i)}) - \mathbf e _{(0, i)}\) can be computed.

Let \(\sigma _1 = (\mathbf t _{(1, 0)} \Vert \mathbf e _{(1, 0)} \Vert \ldots \Vert \mathbf t _{(1, r - 1)} \Vert \mathbf e _{(1, r - 1)})\). We compute \(h_2\) by applying \(H_2\) to the tuple \((D, \sigma _0, h_1, \sigma _1)\) and use it as r binary challenges \(\mathsf {ch} _{2,i} \in \{0, 1\}\).

Now we define \(\sigma _2 = (\mathbf r _{(\mathsf {ch} _{2,i}, i)}, \ldots , \mathbf r _{(\mathsf {ch} _{2,i}, r-1)}, c_{1-\mathsf {ch} _{2,i}}, \ldots , c_{1-\mathsf {ch} _{2, r - 1}}) \). Note that here we also need to include the challenges \(c_{1-\mathsf {ch} _{2,i}}\) that the verifier cannot recompute. We then output \(\sigma = (R, \sigma _0, \sigma _1, \sigma _2)\) as the signature. At 5 bits per \(\mathbb {F}_{31}\) element, the size of the signature is \((2 + r) \cdot k + 5 \cdot r \cdot (2 \cdot n + m)\) bits.

Verification. The verification algorithm takes as input the message m, the signature \(\sigma = (R, \sigma _0, \sigma _1, \sigma _2)\) and the public key \(PK = (\mathcal {S}_F, {{\varvec{PK}}}_{{\varvec{v}}})\). As above, we use R and m to compute D, and derive \(\mathbf {F}\) from \(\mathcal {S}_F\) using \(G_{\mathcal {S}_F}\). As the signature contains \(\sigma _0\), we can compose \(h_1\) and, consequentially, the challenge values \(\alpha _i\) for all r rounds by using \(H_1\). Similarly, the values \(\mathsf {ch} _{2,i}\) are computed by applying \(H_2\) to \((D, \sigma _0, h_1, \sigma _1)\). For each round i, the verifier extracts vectors \(\mathbf t _i\) and \(\mathbf e _i\) (which are always \(\mathbf t _{(1, i)}\) and \(\mathbf e _{(1, i)}\)) from \(\sigma _1\) and \(\mathbf r _i\) from \(\sigma _2\). Depending on \(\mathsf {ch} _{2,i}\), half of the commitments can now be computed:

Extracting the missing commitments \(c_{(1 - \mathsf {ch} _{2,i}, i)}\) from \(\sigma _2\), the verifier now computes \(\sigma _0' = \mathcal {H}(c_{(0, 0)} \Vert c_{(1, 0)} \ldots \Vert c_{(0, r - 1)} \Vert c_{(1, r - 1)})\). For verification to succeed, \(\sigma _0' = \sigma _0\) should hold.

5.3 Security of MQDSS

We now give a security reduction for MQDSS in the ROM. As our results from the last section are non-tight we only prove an asymptotic statement. While this does not suffice to make any statement about the security of a specific parameter choice, it provides evidence that the general approach leads a secure scheme. Also, the reduction is in the ROM, not in the QROM, thereby limiting applicability in the post-quantum setting. As already mentioned in the introduction, we consider it important future work to strengthen this statement.

In the remainder of this subsection we prove the following theorem.

Theorem 5.1

MQDSS is \(\mathsf {\textsf {{EU\text {-}CMA}}}\)-secure in the random oracle model, if
  • the search version of the \(\mathcal {MQ}\) problem is intractable,

  • the hash functions \(\mathcal {H}\), \(H_1\), and \(H_2\) are modeled as random oracles,

  • the commitment functions \(Com_0\) and \(Com_1\) are computationally binding, computationally hiding, and the probability that their output takes a given value is negligible in the security parameter,

  • the pseudorandom generator \(G_{\mathcal {S}_F}\) is modeled as random oracle, and

  • the pseudorandom generators, \(G_{SK}\), and \(G_c\) have outputs computationally indistinguishable from random.

To prove this theorem we would like to apply Theorem 4.8. However, Theorem 4.8 was formulated for a slightly more generic construction. The point is that we apply an optimization originally proposed in [50]. So, in our actual proposal, the parallel composition of the IDS is slightly different as, instead of the commitments, only the hash of their concatenation is sent. Also, the last message now contains the remaining commitments.

While we could have treated this case in Sect. 4, it would have limited the general applicability of the result, as the above optimization is only applicable to schemes with a certain, less generic, structure. However, it is straightforward to redo the proofs from Sect. 4 for the optimized scheme. When modeling the hash function used to compress the commitments as RO, the arguments are exactly the same with one exception. The proof of Lemma 4.12 uses that the commitment scheme – and thereby the first signature element \(\sigma _1\) – only takes a given value with negligible probability. Now this statement follows from the same property of the commitment scheme and the randomness of the RO. Altogether this leads to the following corollary:

Corollary 5.2

(EU-CMA security of q2-signature schemes).Let \(k\in \mathbb {N}\), \(\mathsf {IDS} (1^k)\) a q2-IDS that is honest-verifier zero-knowledge, achieves soundness with constant soundness error \(\kappa \) and has a q2-extractor. Then \(opt\text {-}{}q2\text {-}\mathsf {\textsf {Dss}}(1^k)\), the optimized q2-signature scheme derived by applying Construction 4.7 and the optimization explained above, is existentially unforgeable under adaptive chosen message attacks.

Based on this corollary we can now prove the above theorem.


(of Theorem 5.1 ). Towards a contradiction, assume there exists an adversary \(\mathcal {A}\) that wins the \(\mathsf {\textsf {{EU\text {-}CMA}}}\) game against MQDSS with non-negligible success probability. We show that this implies the existence of an oracle machine \(\mathcal {M} ^\mathcal {A} \) that solves the \(\mathcal {MQ}\) problem, breaks a property of one of the commitment schemes, or distinguishes the outputs of one of the pseudorandom generators from random. We first define a series of games and argue that the difference in success probability of \(\mathcal {A}\) between these games is negligible. We assume that \(\mathcal {M}\) runs \(\mathcal {A}\) in these games.  
Game 0:

Is the \(\mathsf {\textsf {{EU\text {-}CMA}}}\) game for MQDSS.

Game 1:

Is Game 0 with the difference that \(\mathcal {M}\) replaces the outputs of \(G_{SK}\) by random bit strings.

Game 2:

Is Game 1 with the difference that \(\mathcal {M}\) replaces the outputs of \(G_c\) by random bit strings.

Game 3:

Is Game 2 with the difference that \(\mathcal {M}\) takes as additional input a random equation system \(\mathbf {F}\). \(\mathcal {M}\) simulates \(G_{\mathcal {S}_F}\) towards \(\mathcal {A}\), programming \(G_{\mathcal {S}_F}\) such that it returns the coefficients representing \(\mathbf {F}\) upon input of \(\mathcal {S}_F\) and uniformly random values on any other input.

Per assumption, \(\mathcal {A}\) wins Game 0 with non-negligible success probability. Let’s call this \(\epsilon \). If the difference in \(\mathcal {A}\) ’s success probability playing Game 0 or Game 1 was non-negligible, we could use \(\mathcal {A}\) to distinguish the outputs of \(G_{SK}\) from random. The same argument applies for the difference between Game 1 and Game 2, and \(G_c\). Finally, the output distribution of \(G_{\mathcal {S}_F}\) in Game 3 is the same as in previous games. Hence, there is no difference for \(\mathcal {A}\) between Game 2 and Game 3. Accordingly, \(\mathcal {A}\) ’s success probability in these two games is equal.

Now, Game 3 is exactly the \(\mathsf {\textsf {{EU\text {-}CMA}}}\) game for the optimized q2 signature scheme that is derived from \(\mathcal {MQ} \text {-}\mathsf {IDS} \), the 5-pass IDS from [48]. We obtain the necessary contradiction if we can apply Corollary 5.2. For this, it just remains to be shown that \(\mathcal {MQ} \text {-}\mathsf {IDS} \) is a q2-IDS that is honest-verifier zero-knowledge, achieves soundness with constant soundness error \(\kappa \) and has a q2-extractor. Clearly, \(\mathcal {MQ} \text {-}\mathsf {IDS} \) is a q2-IDS under the given assumptions on the commitment schemes. Sakumoto et al. [48] show that \(\mathcal {MQ} \text {-}\mathsf {IDS} \) is honest-verifier zero-knowledge. Theorem 3.1 shows that \(\mathcal {MQ} \text {-}\mathsf {IDS} \) achieves soundness with constant soundness error \(\kappa =\frac{q+1}{2q}\). Finally, the proof of Theorem 3.1 provides a construction of a q2-extractor.    \(\square \)

6 Instantiating the Scheme

In this section, we provide a concrete instance of MQDSS. We discuss a suitable set of parameters to achieve the desired security level, discuss an optimized software implementation, and present benchmark results.

Parameter choice and security analysis. For the 5-pass scheme, the soundness error \(\kappa \) is affected by the size of q. This motivates a field choice larger than \(\mathbb {F}_2\) in order to reduce the number of rounds required. From an implementation point of view, it is beneficial to select a small prime, allowing very cheap multiplications as well as comparatively cheap field reductions. We choose \(\mathbb {F}_{31}\) with the intention of storing it in a 16 bit value – the benefits of which become clear in the next subsection, where we discuss the required reductions.

We now consider the choice of \(\mathcal {MQ} (n,m,\mathbb {F}_{31})\), i.e. the parameters n and m. There are several known generic classical algorithms for solving systems of quadratic equations over finite fields, such as the F4 algorithm [25] and the F5 algorithm [4, 26] using Gröbner basis techniques, the Hybrid Approach [9, 10] that is a variant of the F5 algorithm, or the XL algorithm [15, 18] and variants [56].

Currently, for fields \(\mathbb {F}_q\) where \(q\geqslant 4\), the best known technique for solving overdetermined systems of equations over \(\mathbb {F}_q\) is combining equation solvers with exhaustive search. The Hybrid Approach [9, 10] and the FXL variant of XL [56] use this paradigm. Here we will analyze the complexity using the Hybrid approach. Note that the complexity for the XL family of algorithms is similar [59].

Roughly speaking, for an optimization parameter \(\ell \), using the Hybrid approach one first fixes \(\ell \) among the n variables, and then computes \(q^\ell \) Gröbner bases of the smaller systems in \(n-\ell \) variables. Hence, the improvement over the plain F5 algorithm comes from the proper choice of the parameter \(\ell \). It has been shown in [9] that the best trade-off is achieved when the parameter \(\ell \) is proportional to the number of variables n, i.e. when \(\ell =\tau n\).

Let \(2\leqslant \omega \leqslant 3\) be the linear algebra constant. The complexity of computing a Gröbner basis of a system of m equations in n variables, \(m\geqslant n\), using the F5 algorithm is given by
$$\begin{aligned} C_{F5}(n,m)=\mathcal {O}\left( \left( m\left( {\begin{array}{c}n+d_{reg}(n,m)-1\\ d_{reg}(n,m)\end{array}}\right) \right) ^{\omega }\right) , \end{aligned}$$
where \(d_{reg}(n,m)\) is the degree of regularity of the system which can be approximated as
$$\begin{aligned} d_{reg}(n,m)\approx (\frac{m}{n}-\frac{1}{2}-\sqrt{\frac{m}{n}(\frac{m}{n}-1)})+\mathcal {O}\left( n^{1/3}\right) . \end{aligned}$$
For a fixed \(0<\tau <1\), the complexity of the Hybrid approach is
$$\begin{aligned} C_{Hyb}(n,m,\tau ,d_{reg}(n(1-\tau ),m))= q^{\tau n}\cdot C_{F5}(n(1-\tau ),m,d_{reg,\tau }(n(1-\tau ),m)). \end{aligned}$$
It is well known (and can be seen from the complexity above) that the F5 algorithm as well as the Hybrid approach perform better when the number of equations is bigger than the number of variables, so from this point of view there is no incentive in choosing \(m>n\). On the other hand, if \(m<n\), then we can simply fix \(n-m\) variables and reduce the problem to a smaller one, with m variables. Therefore, in terms of classical security the best choice is \(m=n\).

Following the analysis from [9, 10], we calculated the best trade-off for \(\tau \) for the family of functions \(\mathcal {MQ} (n,n,\mathbb {F}_{31})\), when \(\omega =2.3\). Asymptotically, \(\tau \rightarrow 0.16\), although for smaller values of n (e.g. \(n=32\)) we find \(\tau =0.13\).

Since our goal is classical security of at least 128 bits, we need to choose \(n\ge 51\), so that for any choice of the linear algebra constant \(2\leqslant \omega \leqslant 3\) the Hybrid approach would need at least \(2^{128}\) operations. Note that if we set the more realistic value of \(\omega =2.3\), the minimum is \(n=45\).

For implementation reasons, we choose \(n=64\). In particular, a multiple of 16 suggests efficient register usage for vectorized implementations. In this case, for \(\omega =2.3\), the complexity of the Hybrid approach is \(\approx 2^{177}\) and the best result is obtained for \(\tau =0.14\), which translates to fixing 9 variables in the system.

Regarding post-quantum security, at the moment there is no dedicated quantum algorithm for solving systems of quadratic equations. Instead, we can use Grover’s search algorithm [34] to directly attack the \(\mathcal {MQ}\) problem, or use Grover’s algorithm for the search part in a quantum implementation of the Hybrid method. Note that the later requires an efficient quantum implementation of the F5 algorithm, that we will assume provides no quantum speedup over the classical implementation.

Grover’s algorithm searches for an item in a unordered list of size \(N=2^\mathbf {n}\) that satisfies a certain condition given in the form of a quantum black-box function \(f:\{0,1\}^\mathbf {n}\rightarrow \{0,1\}\). If the condition is satisfied for the i-th item, then \(f(i)=1\), otherwise \(f(i)=0\). The complexity of Grover’s algorithm is \(\mathcal {O}(\sqrt{N/M})\), where M is the number of items in the list that satisfy the condition, i.e. the algorithm provides a quadratic speed-up compared to classical search.

First we will consider a direct application of Grover’s algorithm on the \(\mathcal {MQ}\) problem in question. In this case, f should provide an answer whether a given n-tuple \(\mathbf {x}\) from \(\mathbb {F}^n_{31}\) satisfies the system of equations \(\mathbf {F}(\mathbf {x})=\mathbf {v}\). Since the domain is not Boolean, we need to convert it one, so we get a domain of size \(n\log 31\).

To estimate the complexity of the algorithm, we need the number of solutions M to the given system of equations. Determining the exact M requires exponential time [54], but it was shown in [29] that the number of solutions of a system of n equations in n variables follows the Poisson distribution with parameter \(\lambda =1\). Therefore the expected value is 1. Furthermore, the probability that there are at least M solutions can be estimated as the tail probability of a Poisson random variable \(P[X\geqslant M]\geqslant \frac{(e\lambda )^M}{e^\lambda M^M}=\frac{1}{e}(\frac{e}{M})^M\) which is negligible in M. In practice, we can safely assume that \(M\leqslant 4\), since \(P[M\geqslant 5]\geqslant 2^{-8}\). In total, Grover’s algorithm takes \(\mathcal {O}(2^{n\log 31/2}/4)\approx 2^{156}\) operations.

As said earlier, we can also use a quantum version of the Hybrid approach for \(m=n\). In this case the complexity will be
$$\begin{aligned} C_{Hyb,quantum}(n,\tau ,d_{reg}(n(1-\tau ),n))=\sqrt{\frac{q^{\tau n}}{M}}\cdot C_{F5}(n(1-\tau ),n,d_{reg,\tau }(n(1-\tau ),n)). \end{aligned}$$
Taking again \(M\leqslant 4\), the optimal value for the optimization parameter is \(\tau =0.39\), which means we should fix 25 variables in the system. Hence, the quantum version of the Hybrid method has a time complexity of \(\approx 2^{139}\) operations.

To achieve \(\mathsf {\textsf {{EU\text {-}CMA}}}\) for 128 bits of post-quantum security, we require that \(k^r \le 2^{-256}\), as an adversary could perform a preimage search to effectively control the challenges. As \(\kappa = \frac{q+1}{2q}\) with \(q = 31\), we need \(r = 269\). To complete the scheme, we instantiate the functions \(\mathcal {H}\), \(Com_0\) and \(Com_1\) with SHA3-256, and use SHAKE-128 for \(H_1\), \(H_2\), \(G_{\mathcal {S}_F}\), \(G_c\), and \(G_{SK}\) [7]. In order to convert between the output domain of SHAKE-128 and functions that map to vectors over \(\mathbb {F}_{31}\), we simply reject and resample values that are not in \(\mathbb {F}_{31}\) (effectively applying an instance of the second TSS08 construction from [55]).

We refer to this instance of the scheme as MQDSS-31-64.

Implementation. The central and most costly computation in this signature scheme is the evaluation of \(\mathbf {F}\) (and, by corollary, \(\mathbf {G}\)). The signing procedure requires one evaluation of each for every round, and the verifier needs to compute either \(\mathbf {F}\) (if \(\mathsf {ch} _2 = 0\)) or both \(\mathbf {F}\) and \(\mathbf {G}\) (if \(\mathsf {ch} _2 = 1\)), for each round. Other than these functions, the computational effort is made up of seed expansion, several hash function applications and a small number of additions and subtractions. For SHA3-256 and SHAKE-128, we rely on existing code from the Keccak Code Package [8]. Clearly, the focus for an optimized implementation should be on the \(\mathcal {MQ}\) function. Previous work [12] has shown that modern CPUs offer interesting and valuable methods to efficiently implement this primitive, in particular by exploiting the high level of internal parallelism.

Compared to the binary 3-pass scheme, the implementation of the 5-pass scheme over \(\mathbb {F}_{31}\) presents more challenges. As \(\mathbb {F}_{31}\) does not have closure under regular integer multiplication and addition, results of computations need to be reduced to smaller representations. To avoid having to this too frequently, we generally represent field elements during computation as unsigned 16 bit values. During specific parts of the computation, we vary this representation as needed.

The evaluation of \(\mathbf {F}\) can roughly be divided in two parts: the generation of all monomials, and computation of the resulting polynomials for known monomials. Generating the quadratic monomials based on the given linear monomials requires \(n \cdot \frac{n+1}{2}\) multiplications. For the second part, we require \(m \cdot (n + n \cdot \frac{n+1}{2})\) multiplications to multiply the coefficients of the system parameter with the quadratic monomials, as well as a number of additions to accumulate all results. As the second part is clearly more computationally intensive, the optimization of this part is our primary concern. We describe an approach for the monomial generation in the full version [13] of the paper.

To efficiently compute all polynomials for a given set of monomials, we keep all required data in registers to avoid the cost of register spilling throughout the computation. Given that \(n=m=64\), for this part of the computation we represent the 64 \(\mathbb {F}_{31}\) input values as 8 bit values and the resulting 64 \(\mathbb {F}_{31}\) elements as 16 bit values, costing us 2 and 4 YMM registers respectively. The coefficients of \(\mathbf {F}\) can be represented as a column major matrix with every column containing all coefficients that correspond to a specific monomial, i.e. one for each output value. That would imply that every row of the matrix represents one polynomial of \(\mathbf {F}\). In this representation, each result term is computed by accumulating the products of a row of coefficients with each monomial, which is exactly the same as computing the product of the matrix \(\mathbf {F}\) and the vector containing all monomials. This allows us to efficiently accumulate the output terms, minimizing the required output registers.

In order to perform the required multiplications and additions as quickly as possible, we heavily rely on the AVX2 instruction VPMADDUBSW. In one instruction, this computes two 8 bit SIMD multiplications and a 16 bit SIMD addition. However, this instruction operates on 8 bit input values that are stored adjacently. This requires a slight variation on the representation of \(\mathbf {F}\) described above: instead, we arrange the coefficients of \(\mathbf {F}\) in a column major matrix with 16 bit elements, each corresponding to two concatenated monomials.

When arranging reductions, we must strike a careful balance between preventing overflow and not reducing more often than necessary. As we make extensive use of VPMADDUBSW, which takes both a signed and an unsigned operand to compute the quadratic monomials, we ensure that the input variables for the \(\mathcal {MQ}\) function are unsigned values (in particular: \(\{0,\ldots ,31\}\)). For the coefficients in the system parameter \(\mathbf F \), we can then freely assume the values are in \(\{-15,\ldots ,15\}\), as these are the direct result of a pseudo-random generator. It turns out to be efficient to immediately reduce the quadratic monomials back to \(\{0, \ldots , 31\}\) when they are computed. When we now multiply such a product with an element from the system parameter and add it to the accumulators, the maximum value of each accumulator word will be at most3 \( 64 \cdot 31 \cdot 15 = 29760\). As this does not exceed 32768, we only have to perform reductions on each individual accumulator at the very end.

One should note that [12] approaches this problem from a slightly different angle. In particular, they accumulate each individual output element sequentially, allowing them to keep the intermediate results in the 32 bit representation that is the output of their combined multiplication and addition instructions. This has the natural consequence of also avoiding early reductions.

Benchmark results. The MQDSS-31-64 implementation has been optimized for large Intel processors, supporting AVX2 instructions. Benchmarks were carried out on a single core of an Intel Core i7-4770K CPU, running at 3.5 GHz.

Signature and key sizes. The signature size of MQDSS-31-64 is considerably smaller than that of the 3-pass scheme. The obvious factor in this is the decreased ratio between the element size (which, in packed form, now require \(64 \cdot 5 = 320\) bits each) and the number of rounds, resulting in a signature size of \(2 \cdot 256 + 269 \cdot (256 + (5 \cdot 3 \cdot 64)) = 327\,616\) bits, or 40 952 bytes (39.99 KB). The shape of the keys does not change compared to 3-pass scheme, but since a vector of field elements now requires 320 bits, the public key is 72 bytes. The secret key remains 64 bytes.

Performance. As the \(\mathcal {MQ}\) function is the most costly part of the computation, parameters are chosen in such a way that its performance is maximized. The required number of multiplications and additions (expressed as functions of n and m) does not change dramatically compared to the 3-pass baseline4, but the actual values n and m are only a quarter of what they were. As the relation between n and m and the number of multiplications is quadratic for the monomials and cubic for the system parameter masking, and we see only a linear increase in the number of registers needed to operate on, the entire sequence of multiplications and additions becomes much cheaper. This especially impacts operations that involve the accumulators. As the representation allows us to keep reductions out of this innermost repeated loop, we perform (only) \(\frac{67 \cdot 4}{2} + 4 = 136\) reductions5 throughout the main computation and 66 when preparing quadratic monomials. As we were able to arrange the registers in such a way that they do not need to rotate across multiple registers, we greatly reduce the number of rotations required compared to the 3-pass scenario. Furthermore, we note that we use a total of \(67 \cdot 16 \cdot 4 = 4288\) VPMADDUBSW instructions for the core computations.

For one iteration of the \(\mathcal {MQ}\) function F, we measure 6 616 cycles (\(\mathbf G \) is slightly less costly, at 6 396 cycles). We measure a total of 8 510 616 cycles for the complete signature generation. Key generation costs 1 826 612 cycles, and verification consumes 5 752 612 cycles. On the given platform, that translates to roughly 2.43 ms, 0.52 ms and 1.64 ms, respectively. Verification is expected to require on average \(\frac{3}{2}\) calls to an \(\mathcal {MQ}\) function per round, whereas signature generation always requires two. This explains the ratio; note that both signer and verifier incur additional costs besides the \(\mathcal {MQ}\) functions, e.g. for seed expansion.

In order to compare these results to the state of the art, we consider the performance figures reported in [12]. In particular, we examine the Rainbow(31, 24, 20, 20) instance, as the ‘public map’ in this scheme is effectively the \(\mathcal {MQ}\) function over \(\mathbb {F}_{31}\) with \(n = 64\), as used above. The number of equations differs (i.e. \(m = 40\) as opposed to \(m = 64\)), but this can be approximated by normalizing linearly. In [12], the authors report a time measurement of \(17.7\, \mu {}s\), which converts to 50 144 cycles on their 2.833 GHz Intel C2Q Q9550. After normalizing for m, this amounts to 80 230 cycles. Results from the eBACS benchmarking project further show that running the Rainbow verification function from [12] on a Haswell CPU requires approximately 46 520 cycles (and thus 74 432 after normalizing); verification is dominated by the public map. Using their (by now arguably outdated) SSE2-based code to evaluate a public map with \(m = 64\) consumes 60 968 cycles on our Intel Core i7-4770K. All of these results provide confidence in the fact that our implementation, which makes extensive use of AVX2 instructions, is performing in line with expectations.


  1. 1.

    Sakumoto et al. [48] also sketched a proof that their 5-pass protocol is argument of knowledge when Com is computationally binding. Our security arguments rely on the weaker notion of soundness, therefore we include an appropriate proof.

  2. 2.

    Note that the concatenation of all \(\alpha _i\) was previously referred to as \(\mathsf {ch} _1\).

  3. 3.

    This follows from the fact that we combine 64 such monomials in two YMM registers.

  4. 4.

    A slight difference is introduced by cancellation of the monomials in the \(\mathbb {F}_2\) setting.

  5. 5.

    This follows from the fact that we need a total of \(\frac{64+64\cdot 65}{2 \cdot 32} = 67\) YMM registers worth of space to store the monomials and perform 4 reductions after accumulating 2 YMM monomials.



The authors would like to thank Marc Fischlin for helpful discussions, the anonymous reviewers for valuable comments, Wen-Ding Li for his contributions to the software, and Arno Mittelbach for the cryptocode package.


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Copyright information

© International Association for Cryptologic Research 2016

Authors and Affiliations

  1. 1.Department of Electrical EngineeringNational Taiwan UniversityTaipeiTaiwan
  2. 2.Research Center for Information Technology InnovationAcademia SinicaTaipeiTaiwan
  3. 3.Department of Mathematics and Computer ScienceTechnische Universiteit EindhovenEindhovenThe Netherlands
  4. 4.Digital Security GroupRadboud UniversityNijmegenThe Netherlands
  5. 5.Faculty of Computer Science and Engineering“Ss. Cyril and Methodius” UniversitySkopjeRepublic of Macedonia

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