Multilinear Maps from Obfuscation
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Abstract
We provide constructions of multilinear groups equipped with natural hard problems from indistinguishability obfuscation, homomorphic encryption, and NIZKs. This complements known results on the constructions of indistinguishability obfuscators from multilinear maps in the reverse direction.
We provide two distinct, but closely related constructions and show that multilinear analogues of the \(\mathrm {DDH} \) assumption hold for them. Our first construction is symmetric and comes with a \(\kappa \)linear map \(\mathbf {e}: {{{\mathbb {G}}}}^\kappa \longrightarrow {{\mathbb {G}}} _T\)for primeorder groups \({{\mathbb {G}}} \) and \({{\mathbb {G}}} _T\). To establish the hardness of the \(\kappa \)linear \(\mathrm {DDH} \) problem, we rely on the existence of a base group for which the \((\kappa 1)\)strong \(\mathrm {DDH} \) assumption holds. Our second construction is for the asymmetric setting, where \(\mathbf {e}: {{\mathbb {G}}} _1 \times \cdots \times {{\mathbb {G}}} _{\kappa } \longrightarrow {{\mathbb {G}}} _T\) for a collection of \(\kappa +1\) primeorder groups \({{\mathbb {G}}} _i\) and \({{\mathbb {G}}} _T\), and relies only on the standard \(\mathrm {DDH} \) assumption in its base group. In both constructions the linearity \(\kappa \) can be set to any arbitrary but a priori fixed polynomial value in the security parameter.
We rely on a number of powerful tools in our constructions: (probabilistic) indistinguishability obfuscation, dualmode NIZK proof systems (with perfect soundness, witness indistinguishability and zero knowledge), and additively homomorphic encryption for the group \(\mathbb {Z}_N^{+}\). At a high level, we enable “bootstrapping” multilinear assumptions from their simpler counterparts in standard cryptographic groups, and show the equivalence of IO and multilinear maps under the existence of the aforementioned primitives.
Keywords
Multilinear map Indistinguishability obfuscation Homomorphic encryption Decisional Diffie–Hellman Groth–Sahai proofs1 Introduction
1.1 Main Contribution
In this paper, we explore the relationship between multilinear maps and obfuscation. Our main contribution is a construction of multilinear maps for groups of prime order equipped with natural hard problems, using indistinguishability obfuscation (IO) in combination with other tools, namely NIZK proofs, homomorphic encryption, and a base group \({{\mathbb {G}}} _{0}\) satisfying a mild cryptographic assumption. This complements known results in the reverse direction, showing that various forms of indistinguishability obfuscation can be constructed from multilinear maps [GGH+13b, CLTV15, Zim15]. The relationship between IO and multilinear maps is a very natural question to study, given the rich diversity of cryptographic constructions that have been obtained from both multilinear maps and obfuscation, and the apparent fragility of current constructions for multilinear maps. More on this below.
We provide two distinct but closely related constructions. One is for multilinear maps in the symmetric setting, that is nondegenerate multilinear maps \(\mathbf {e}: {{{\mathbb {G}}} _1}^\kappa \longrightarrow {{\mathbb {G}}} _T\) for groups \({{\mathbb {G}}} _1\) and \({{\mathbb {G}}} _T\) of prime order N. Our construction relies on the existence of a base group \({{\mathbb {G}}} _0\) in which the \((\kappa 1)\text {}\mathrm {SDDH} \) assumption holds—this states that, given a \(\kappa \)tuple of \({{\mathbb {G}}} _0\)elements \((g,g^\omega ,\ldots ,g^{\omega ^{\kappa 1}})\), we cannot efficiently distinguish \(g^{\omega ^{\kappa }}\) from a random element of \({{\mathbb {G}}} _0\). Under this assumption, we prove that the \(\kappa \text {}\mathrm {MDDH} \) problem, a natural analogue of the DDH problem as stated below, is hard.
(The \(\kappa \text {}\mathrm {MDDH} \) problem, informal). Given a generator \(g_1\) of \({{\mathbb {G}}} _1\) and \(\kappa +1\) group elements \(g_1^{a_i}\) in \({{\mathbb {G}}} \) with \(a_i{{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}\mathbb {Z}_N\), distinguish \({\mathbf {e} (g_1,\ldots ,g_1)}^{\prod _{i=1}^{\kappa +1}a_i}\) from a random element of \({{\mathbb {G}}} _T\).
This problem can be used as the basis for several cryptographic constructions [BS03] including, as the by now the classic example of multiparty noninteractive key exchange (NIKE) [GGH13a].
Our other construction is for the asymmetric setting, that is multilinear maps \(\mathbf {e}: {{\mathbb {G}}} _1 \times \cdots \times {{\mathbb {G}}} _{\kappa } \longrightarrow {{\mathbb {G}}} _T\) for a collection of \(\kappa \) groups \({{\mathbb {G}}} _i\) and \({{\mathbb {G}}} _T\) all of prime order N. It uses a base group \({{\mathbb {G}}} _0\) in which we require only that the standard DDH assumption holds. For this construction, we show that a natural asymmetric analogue of the \(\kappa \text {}\mathrm {MDDH} \) assumption holds (wherein all but two of the \(\kappa +1\) group elements input to \(\mathbf {e} \) come from distinct groups).
In Sect. 7, we also show the intractability of the rank problem for our construction for multilinear maps in the symmetric setting; this is a generalization of \(\mathrm {DDH} \)like problems to matrices that has proven to be useful in cryptographic constructions [BHHO08, NS09, GHV12, BLMR13, EHK+13].
At a high level, then, our constructions are able to “bootstrap” from rather mild assumptions in a standard cryptographic group to much stronger multilinear assumptions in a group (or groups, in the asymmetric setting) equipped with a \(\kappa \)linear map. Here \(\kappa \) is fixed upfront at construction time, but is otherwise unrestricted. Of course, such constructions cannot be expected to come “for free,” and we need to make use of powerful tools including probabilistic IO (PIO) for obfuscating randomized circuits [CLTV15], dualmode NIZK proofs enjoying perfect soundness (for a binding CRS), perfect witness indistinguishability (for a hiding CRS), and perfect zero knowledge, and additive homomorphic encryption for the group \((\mathbb {Z}_N,+)\) (or alternatively, a perfectly correct FHE scheme). It is an important open problem arising from our work to weaken the requirements on, or remove altogether, these additional tools.
1.2 General Approach
Our approach to obtaining multilinear maps in the symmetric setting is as follows (with many details to follow in the main body). Let \({{\mathbb {G}}} _0\) with generator \(g_0\) be a group of prime order N in which the \((\kappa 1)\text {}\mathrm {SDDH} \) assumption holds.
We work with redundant encodings of elements h of the base group \({{\mathbb {G}}} _0\) of the form \(h = g_0^{x_0}{(g_0^{\omega })}^{x_1}\) where \(g_0^{\omega }\) comes from a \((\kappa 1)\text {}\mathrm {SDDH} \) instance; we write \({{\mathbf {x}}} = (x_0,x_1)\) for the vector of exponents representing h. Then \({{\mathbb {G}}} _1\) consists of all strings of the form \((h,{{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}},{{\pi }})\) where \(h \in {{\mathbb {G}}} _0\), ciphertext \({{\mathbf {c}}_{1}} \) is a homomorphic encryption under public key \({{ pk }} _1\) of a vector \({{\mathbf {x}}} \) representing h, ciphertext \({{\mathbf {c}}_{2}} \) is a homomorphic encryption under a second public key \({{ pk }} _2\) of another vector \({{\mathbf {y}}} \) also representing h, and \({{\pi }} \) is a NIZK proof showing consistency of the two vectors \({{\mathbf {x}}} \) and \({{\mathbf {y}}} \), i.e., a proof that the plaintexts \({{\mathbf {x}}} \), \({{\mathbf {y}}} \) underlying \({{\mathbf {c}}_{1}} \), \({{\mathbf {c}}_{2}} \) encode the same group element h. Note that each element of the base group \({{\mathbb {G}}} _0\) is multiply represented when forming elements in \({{\mathbb {G}}} _1\), but that equality of group elements in \({{\mathbb {G}}} _1\) is easy to test. An alternative viewpoint is to consider \(({{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}},{{\pi }})\) as being auxiliary information accompanying element \(h \in {{\mathbb {G}}} _0\); we prefer the perspective of redundant encodings, and our abstraction in Sect. 3 is stated in such terms. When viewed in this way, our approach can be seen as closely related to the Naor–Yung paradigm for constructing CCAsecure PKE [NY90].
Addition of two elements in \({{\mathbb {G}}} _1\) is carried out by an obfuscation of a circuit \(C_\mathrm {Add}\) that is published along with the groups. It has the secret keys \({{ sk }} _1, {{ sk }} _2\) hardcoded in; it first checks the respective proofs, then uses the additive homomorphic property of the encryption scheme to combine ciphertexts, and finally uses the secret keys \({{ sk }} _1, {{ sk }} _2\) as witnesses to generate a new NIZK proof showing equality of encodings. Note that the new encoding is as compact as that of the two input elements.
The multilinear map on inputs \((h_i,{{\mathbf {c}}_{i,1}},{{\mathbf {c}}_{i,2}},{{\pi }} _i)\) for \(1 \le i \le \kappa \) is computed using the obfuscation of a circuit \(C_\mathrm {Map}\) that has \({{ sk }} _1\) and \(\omega \) hardcoded in. This allows \(C_\mathrm {Map}\) to “extract” full exponents of \(h_i\) in the form \((x_{i,1}+\omega \cdot x_{i,2})\) from \({{\mathbf {c}}_{i,1}} \), and thereby compute the element \(g_0^{\prod _i (x_{i,1}+\omega \cdot x_{i,2})}\). This is defined to be the output of our multilinear map \(\mathbf {e} \), and so our target group \({{\mathbb {G}}} _T\) is in fact \({{\mathbb {G}}} _0\), the base group. The multilinearity of \(\mathbf {e} \) follows immediately from the form of the exponent.
In the asymmetric case, the main difference is that we work with different values \(\omega _i\) in each of our input groups \({{\mathbb {G}}} _i\). However, the groups are all constructed via redundant encodings, just as above.
This provides a highlevel view of our approach, but no insight into why the approach achieves our aim of building multilinear maps with associated hard problems. Let us give some intuition on why the \(\kappa \text {}\mathrm {MDDH} \) problem is hard in our setting. We transform a \(\kappa \text {}\mathrm {MDDH} \) tuple \({{\mathbf {h}}} = ({(g_1^{a_i})}_{i \le \kappa +1},g_T^{d})\), where d is the product of the \(a_i \in \mathbb {Z}_N\), \(g_1\) is in the “encoded” form above, thus \(g_1 = (h_1,{{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}},{{\pi }})\), and \(g_T\) is a generator of \({{\mathbb {G}}_{T}} ={{\mathbb {G}}} _{0}\), into another \(\kappa \text {}\mathrm {MDDH} \) tuple \({{\mathbf {h}}} '\) with exponents \(a'_i = a_i+\omega \) for \(i \le \kappa \). This means that the exponent of the challenge element in the target group \(d' = \prod _1^\kappa (a_i +\omega )a_{\kappa +1}\) can be seen as a degree \(\kappa \) polynomial in \(\omega \). Therefore, with the knowledge of the \(a_i\) and a \((\kappa 1)\text {}\mathrm {SDDH} \) challenge, with \(\omega \) implicit in the exponent, we are able to randomize \(g_T^{d'}\) replacing \(g_T^{\omega ^\kappa }\) with a uniform value.
Nevertheless, in the preceding simplistic argument we have made two assumptions. The first is that we are able to provide an obfuscation of a circuit \(C_\mathrm {Map}'\) that has the same functionality as \(C_\mathrm {Map}\) over \({{\mathbb {G}}_{1}}\) without the explicit knowledge of \(\omega \). We resolve this by showing a way of evaluating the \(\kappa \)linear map on any elements of \({{\mathbb {G}}_{1}} \) using only the powers \(g_0^{\omega ^i}\) for \(1 \le i \le \kappa 1\), and vectors extracted from the accompanying ciphertexts, and then applying \(\mathrm {IO}\) to the two circuits.^{1}
The second assumption we made is that we can indeed switch from \({{\mathbf {h}}} \) to \({{\mathbf {h}}} '\) without being noticed. In other words, that the vectors \({{\mathbf {x}}} _i\), \({{\mathbf {y}}_{i}} \) representing \(g^{a_i}\) can be replaced (without being noticed) with vectors \({{\mathbf {h}}_{i}} '\) whose second coordinate is always fixed. Intuitively this is based on the \(\mathrm {IND{\text {}}CPA} \) security of the FHE scheme, but in order to give a successful reduction we also have to change the circuit \(C_\mathrm {Add}\) (since \(C_\mathrm {Add}\) uses both decryption keys). We show two ways to do this: one is based on probabilistic indistinguishability obfuscation [CLTV15], and the other uses only (deterministic) indistinguishability obfuscation, and additionally exploits the specific structure of a particular (pairingbased) NIZK implementation due to Groth and Sahai [GS08].
We note that in this work we do not construct graded encoding schemes as in [GGH13a]. That is, we do not construct maps from \({{\mathbb {G}}} _i \times {{\mathbb {G}}} _j\) to \({{\mathbb {G}}} _{i+j}\). On the other hand, our construction is noiseless and is closer to multilinear maps as defined by Boneh and Silverberg [BS03].
1.3 Attacks on Multilinear Maps
Multilinear maps have been in a state of turmoil, with the discovery of attacks [CHL+15, HJ15, CLR15, MF15, Cor15] against the GGH13 [GGH13a], CLT [CLT13, CLT15] and GGH15 [GGH15] proposals. Hence, our confidence in constructions for graded encoding schemes (and thereby multilinear maps) has been shaken. On the other hand, when IO is constructed from graded encoding schemes via Barrington’s theorem [GGH+13b] or dualinput straddling sets [AB15, Zim15], then none of the known attacks on graded encoding schemes seem to apply [CGH+15]. Indeed, when building IO from multilinear maps one restricts the pool of available operations to an attacker by fixing a circuit a priori which means that certain “interesting” elements cannot be (easily) constructed. Hence, currently it is perhaps more plausible to assume that IO exists than it is to assume that secure multilinear maps exist. However, we stress that more cryptanalysis of IO constructions is required to investigate what security they provide.
Moreover, even though current constructions for IO rely on graded encoding schemes, it is not implausible that alternative routes to achieving IO without relying on multilinear maps will emerge in due course. And setting aside the novel applications obtained directly from IO, multilinear maps, and more generally graded encoding schemes, have proven to be very fruitful as constructive tools in their own right (cf. [BS03, PTT10], resp., [FHPS13, GGH+13c, HSW13] and [GGSW13, BWZ14, TLL14, BLR+15]). This rich set of applications coupled with the current uncertainty over the status of graded encoding schemes and multilinear maps provides additional motivation to ask what additional tools are needed in order to upgrade IO to multilinear maps. As an additional benefit, we upgrade (via IO) noisy graded encoding schemes to clean multilinear maps—sometimes now informally called “dream” or “ideal” multilinear maps.
1.4 Related Work
The closest related work to ours is that of Yamakawa et al. [YYHK14, YYHK15]; indeed, their work was the starting point for ours. Yamakawa et al. construct a selfpairing map, that is a bilinear map from \({{\mathbb {G}}} \times {{\mathbb {G}}} \) to \({{\mathbb {G}}} \); multilinear maps can be obtained by iterating their selfpairing. Their work is limited to the RSA setting. It uses the group of signed quadratic residues modulo a Blum integer N, denoted \(QR_N^{+}\), to define a pairing function that, on input elements \(g^x\), \(g^y\) in \(QR_N^{+}\), outputs \(g^{2xy}\). In their construction, elements of \(QR_N^{+}\) are augmented with auxiliary information to enable the pairing computation—in fact, the auxiliary information for an element \(g^x\) is simply an obfuscation of a circuit for computing the 2xth power modulo \({{\mathrm {ord}}} (QR_N^{+})\), and the pairing is computed by evaluating this circuit on an input \(g^y\) (say). The main contribution of [YYHK14] is in showing that these obfuscated circuits leak nothing about x or the group order.
A nice feature of their scheme is that the degree of linearity \(\kappa \) that can be accommodated is not limited upfront in the sense that the pairing output is also a group element to which further pairing operations (derived from auxiliary information for other group elements) can be applied. However, the construction has several drawbacks. First, the element output by the pairing does not come with auxiliary information.^{2} Second, the size of the auxiliary information for a product of group elements grows exponentially with the length of the product, as each single product involves computing the obfuscation of a circuit for multiplying, with its inputs already being obfuscated circuits. Third, the main construction in [YYHK14] only builds hard problems for the selfpairing of the computational type (in fact, they show the hardness of the computational version of the \(\kappa \text {}\mathrm {MDDH} \) problem in \(QR_N^{+}\) assuming that factoring is hard). Still, this is sufficient for several cryptographic applications.
In contrast, our construction is generic with respect to its platform group. Furthermore, the equivalent of the auxiliary information in our approach does not itself involve any obfuscation. Consequently, the description of a product of group elements stays compact. Indeed, given perfect additive homomorphic encryption for \((\mathbb {Z}_p,+)\), we can perform arbitrary numbers of group operations in each component group \({{\mathbb {G}}} _i\). It is an open problem to find a means of augmenting our construction with the equivalent of auxiliary information in the target group \({{\mathbb {G}}} _T\), to make our multilinear maps amenable to iteration and thereby achieve graded maps as per [GGH13a, CLT13].
2 Background
The security parameter is denoted by \(\lambda \in \mathbb {N}\). We assume that \(\lambda \) is an implicit input given in unary to all algorithms. Given a randomized algorithm \(\mathcal {A} \) we denote the action of running \(\mathcal {A} \) on inputs \((x_1,\ldots )\) with fresh random coins r and assigning the output(s) to \(y_1,\ldots \) by \((y_1,\ldots ) {{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}\mathcal {A} (x_1,\ldots ;r)\), and for a finite set X, we denote the action of sampling a uniformly random element x from X by \(x {{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}X\). Vectors are written in boldface \(\mathbf {x}\) and by slight abuse of notation, running algorithms on vectors of elements indicates componentwise operation. A realvalued function \(\mu (\lambda )\) is negligible if \(\mu (\lambda ) \in \mathcal {O}(\lambda ^{\omega (1)})\). The set of all negligible functions is denoted by \(\textsc {Negl}\).
2.1 Homomorphic PublicKey Encryption
Scheme \(\mathrm {\Pi }:=({{\mathbf {Gen}}},{{\mathbf {Enc}}},{{\mathbf {Dec}}},{{\mathbf {Eval}}})\) denotes a homomorphic publickey encryption (HPKE) with message space \(\{0,1\}^\lambda \), where \({{\mathbf {Eval}}} \) is a deterministic algorithm. We require \(\mathrm {\Pi }\) to be \(\mathrm {IND{\text {}}CPA}\), perfectly correct, and compact, and also assume that the secret keys are the random coins used in key generation; this will allow to check key pairs for validity.
2.2 Obfuscators
An algorithm \({{\mathbf {Obf}}} \) is an obfuscator for circuit class \({{\mathcal {C}}} =\{{{\mathcal {C}}} _\lambda \}_{\lambda \in \mathbb {N}}\) if for any \({{ m }} \in \{0,1\}^\lambda \), \(C \in {{\mathcal {C}}} _\lambda \), and \(\overline{C} {{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}{{\mathbf {Obf}}} (C)\) we have that \(C({{ m }}) = \overline{C}({{ m }})\). The security of \({{\mathbf {Obf}}} \) with respect a class \({{\mathcal {C}}} \) requires that no ppt adversary \(\mathcal {A}:=(\mathcal {A} _1,\mathcal {A} _2)\) can distinguish the obfuscation of two circuits in \({{\mathcal {C}}}\) with noticeable probability. We will consider two notions of obfuscation depending on the class of permissible adversaries. The first notion is functional equivalence, whereby the two circuits any sampled circuits \(C_1\), \(C_2\) must satisfy \(C({{ m }}) = C({{ m }})\) for all \({{ m }} \). We will write \({{\mathbf {IO}}}\) for obfuscator whenever this level of security is assumed. The second notion is Xind sampling [CLTV15], which, roughly speaking, requires the existence of a domain subset \(\mathcal {X}\) of size at most X such that the two circuits are functionally equivalent outside \(\mathcal {X}\) and furthermore within \(\mathcal {X}\) the outputs are indistinguishable. We will write \(\mathbf {PIO}\) for this case.
2.3 DualMode NIZK Proof Systems
In our constructions we will be relying on special types of noninteractive zeroknowledge proof systems [GS08]. These systems have “dualmode” common reference string (CRS) generation algorithms that produce indistinguishable CRSs in the “binding” and “hiding” modes. The standard prototype for such schemes are pairingbased Groth–Sahai proofs [GS08], and using a generic NP reduction to the satisfiability of quadratic equations we can obtain a suitable proof system for any NP language. We formalize the syntax and security of such proof systems next.
Syntax. A relation with setup is a pair of ppt algorithms \(({{\mathbf {S}}},{{\mathbf {R}}})\) such that \({{\mathbf {S}}} (1^\lambda )\) outputs \(({{ gpk }},{{ gsk }})\) and \({{\mathbf {R}}} ({{ gpk }},x,w)\) is a ternary relation and outputs a bit \(b\in \{0,1\}\). A dualmode noninteractive zeroknowledge (NIZK) proof system \({{\mathrm {\Sigma }}} \) for \(({{\mathbf {S}}},{{\mathbf {R}}})\) consists of five algorithms as follows. (1) Algorithm \({{\mathbf {BCRS}}} ({{ gpk }},{{ gsk }})\) outputs a (binding) common reference string \({{ crs }} \) and an extraction trapdoor \({{ td }_{ext}} \); (2) \({{\mathbf {HCRS}}} ({{ gpk }},{{ gsk }})\) outputs a (hiding) common reference string \({{ crs }} \) and a simulation trapdoor \({{ td }_{zk}} \); (3) \({{\mathbf {Prove}}} ({{ gpk }},{{ crs }},x,w)\), on input \({{ crs }} \), an instance x, and a witness w for \(x\), outputs a proof \(\pi \); (4) \({{\mathbf {Verify}}} ({{ gpk }},{{ crs }},x,\pi )\) on input a bit string \({{ crs }} \), an instance x, and a proof \(\pi \), outputs accept or reject; (5) \({{\mathbf {WExt}}} ({{ td }_{ext}},x,\pi )\) on input an extraction trapdoor, an instance \(x\), and a proof \(\pi \), outputs a witness \(w\) ^{3}; and (6) \({{\mathbf {Sim}}} ({{ td }_{zk}},{{ crs }},x)\) on input the simulation trapdoor \({{ td }_{zk}} \), the CRS \({{ crs }} \), and an instance x, outputs a simulated proof \({{\pi }} \).
Security. We require a dualmode NIZK to meet the following requirements. (1) binding and hiding CRS indistinguishability; (2) perfect completeness under the hiding and binding modes; (3) perfect soundness under the binding mode; (4) perfect extractability under the binding mode; (5) perfect witnessindistinguishability under the hiding mode; and (6) perfect zeroknowledge under the binding mode.
2.4 Hard Membership Problems
Finally, we will use languages with hard membership problems. More specifically, we say that a family \(\mathcal {L}=\{\mathcal {L}_\lambda \}\) of families \(\mathcal {L}_\lambda =\{L\}\) of languages \(L\subseteq U\) in a universe \(U=U_\lambda \) has a hard subset membership problem if the following holds. Namely, we require that no ppt algorithm can efficiently distinguish between \(x{{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}L\) for \(L{{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}\mathcal {L}_\lambda \), and \(x{{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}U=U_\lambda \).
3 Multilinear Groups with Nonunique Encodings
Before presenting our constructions, we formally introduce what we mean by a multilinear group (MLG) scheme. Our abstraction is a direct adaptation of the “cryptographic” MLG setting of [BS03] to a setting where group elements have nonunique encodings. In our abstraction, on top of the procedures needed for generating, manipulating and checking group elements, we introduce an equalitychecking procedure which generalizes that for groups with unique encodings.
Syntax. A multilinear group (MLG) scheme \(\varGamma \) consists of six ppt algorithms as follows.

\(\mathbf {Setup} (1^\lambda ,1^\kappa )\) : This is the setup algorithm. On input the security parameter \(1^\lambda \) and the multilinearity \(1^\kappa \), it outputs the group parameters \({{ pp }} \). These parameters include generators \( g _1,\ldots , g _{\kappa +1}\), identity elements \({\mathsf {1}}_{1},\ldots ,{\mathsf {1}}_{\kappa +1}\), and integers \(N_1,\ldots ,N_{\kappa +1}\) (which will represent group orders). We assume \({{ pp }} \) is provided to the various algorithms below.

\(\mathbf {Val} _i({{h}})\) : This is the validity testing algorithm. On input (the group parameters and) a group index \(1 \le i \le \kappa +1\) and a string \({{h}} \in \{0,1\}^*\), it returns \(b\in \{\top ,\bot \}\). We define \({{\mathbb {G}}} _i\), which is also parameterized by \({{ pp }} \), as the set of all \({{h}} \) for which \(\mathbf {Val} _i({{h}})\) holds. We write \({{h}} \in {{\mathbb {G}}} _i\) when \(\mathbf {Val} _i({{h}})\) holds and refer to such strings as group elements (since we will soon impose a group structure on \({{\mathbb {G}}} _i\)). We require that the bitstrings in \({{\mathbb {G}}} _i\) have lengths that are polynomial in \(1^\kappa \) and \(1^\lambda \), a property that we refer to as compactness.

\(\mathbf {Eq} _i({{h}} _1,{{h}} _2)\) : This is the equality testing algorithm. On input two valid group elements \({{h}} _1,{{h}} _2 \in {{\mathbb {G}}} _i\), it outputs a Boolean value \(b \in \{\top ,\bot \}\).^{4} We require \(\mathbf {Eq} _i\) to define an equivalence relation. We say that the group has unique encodings if \(\mathbf {Eq} _i\) simply checks the equality of bit strings. We write \({{\mathbb {G}}} _i({{h}})\) for the set of all \({{h}} ' \in {{\mathbb {G}}} _i\) such that \(\mathbf {Eq} _i({{h}},{{h}} ')=\top \); for any such \({{h}}, {{h}} '\) in \({{\mathbb {G}}} _i\) we write \({{h}} = {{h}} '\); sometimes we write \({{h}} = {{h}} '\) in \({{\mathbb {G}}} _i\) for clarity. Since “\(=\)” refers to equality of bitstrings as well as equivalence under \(\mathbf {Eq} _i\) we will henceforth will write “as bitstrings” when we mean equality in that sense. We require \({{\mathbb {G}}} _i/\mathbf {Eq} _i\), the number of equivalence classes into which \(\mathbf {Eq} _i\) partitions \({{\mathbb {G}}} _i\), to be finite and equal to \(N_i\) (where \(N_i\) comes from \({{ pp }} \)). Note that equality testing algorithms \(\mathbf {Eq} _i\) for \(1 \le i \le \kappa \) can be derived from one for \(\mathbf {Eq} _{\kappa +1}\) using the multilinear map \(\mathbf {e} \) defined below, provided \(N_{\kappa +1}\) is prime.

\(\mathbf {Op} _i({{h}} _1,{{h}} _2)\) : This algorithm will define our group operation. On input two valid group elements \({{h}} _1,{{h}} _2 \in {{\mathbb {G}}} _i\) it outputs \({{h}} \in {{\mathbb {G}}} _i\). We write \({{h}} _1{{h}} _2\) in place of \(\mathbf {Op} _i({{h}} _1,{{h}} _2)\) for simplicity. We require that \(\mathbf {Op} _i\) respect the equivalence relations \(\mathbf {Eq} _i\), meaning that if \({{h}} _1 = {{h}} _2\) in \({{\mathbb {G}}} _i\) and \({{h}} \in {{\mathbb {G}}} _i\), then \({{h}} _1{{h}} = {{h}} _2{{h}} \) in \({{\mathbb {G}}} _i\). We also demand that \({{h}} _1 {{h}} _2 = {{h}} _2 {{h}} _1\) in \({{\mathbb {G}}} _i\) (commutativity), for any third \({{h}} _3 \in {{\mathbb {G}}} _i\) we require \({{h}} _1 ({{h}} _2 {{h}} _3) = ({{h}} _1 {{h}} _2){{h}} _3\) in \({{\mathbb {G}}} _i\) (associativity) and \({{h}} _1 {\mathsf {1}}_i = {{h}} _1\) in \({{\mathbb {G}}} _i\). These requirements ensure that \({{\mathbb {G}}} _i/\mathbf {Eq} _i\) acts as an Abelian group of order \(N_i\) with respect to the operation induced by \(\mathbf {Op} _i\) and identity element \({\mathsf {1}}_i\). The algorithm \(\mathbf {Op} \) gives rise to an exponentiation algorithm \(\mathbf {Exp} _i({{h}},z)\) that on input \({{h}} \in {{\mathbb {G}}} _i\) and \(z \in \mathbb {N}\) outputs an \(h' \in {{\mathbb {G}}} _i\) such that \(h' = h \cdots h\) in \({{\mathbb {G}}} _i\) with z occurrences of \({{h}} \). When no h is specified, we assume \({{h}} = g _i\). This algorithm runs in polynomial time in the length of z. We denote \(\mathbf {Exp} _i({{h}},z)\) by \({{h}} ^z\) and define \({{h}} ^0:={\mathsf {1}}_i\). Note that under the definition of \(N_i\) for any \({{h}} \in {{\mathbb {G}}} _i\) we have that \(\mathbf {Exp} _i({{h}},N_i)={\mathsf {1}}_i\).^{5} This in turn leads to an inversion algorithm \(\mathbf {Inv} _i({{h}})\) that on input \({{h}} \in {{\mathbb {G}}} _i\) outputs \({{h}} ^{N_i1}\). We insist that \(g_i\) in fact has order \(N_i\), so that (the equivalence class containing) \(g_i\) generates \({{\mathbb {G}}} _i/\mathbf {Eq} _i\). We do not treat the case where the \(N_i\) are unknown but the formalism is easily extended to include it by adding an explicit inversion algorithm and by replacing \(N_i\) in \({{ pp }} \) with an approximation (which may be needed for sampling purposes). We use the bracket notion [EHK+13] to denote an element \({{h}} = g _i^x\) in \({{\mathbb {G}}} _i\) with \([ x ] _i\). When using this notation, we will write the group law additively. This notation will be convenient in the construction and analysis of our MLG schemes. For example \({[z]}_i + {[z']}_i\) succinctly denotes \(\mathbf {Op} _i(\mathbf {Exp} ( g _i,z),\mathbf {Exp} ( g _i,z'))\). Note that when writing \({[z]}_i\) it is not necessarily the case that z is explicitly known.
 \(\mathbf {e} (h_1,\ldots ,h_\kappa )\) : This is the multilinear map algorithm. For \(\kappa \) group elements \({{h}} _i \in {{\mathbb {G}}} _i\) as input, it outputs \({{h}} _{\kappa +1} \in {{\mathbb {G}}} _{\kappa +1}\). We demand that for any \(1 \le j \le \kappa \) and any \({{h}} '_j \in {{\mathbb {G}}} _j\)We also require the map to be nondegenerate in the sense that for some tuple of elements as input the multilinear map outputs an element of \({{\mathbb {G}}} _{\kappa +1}\) not in the equivalence class of \({\mathsf {1}}_{\kappa +1}\). (This implies that \(\mathbf {e} \) is surjective onto \({{\mathbb {G}}} _{\kappa +1}/\mathbf {Eq} _{\kappa +1}\) when \(N_i\) is prime, but need not imply surjectivity when \(N_{\kappa +1}\) is composite.) We call an MLG scheme symmetric if the group algorithms are independent of the group index for \(1 \le i \le \kappa \) and the \(\mathbf {e} \) algorithm is invariant under permutations of its inputs. That is for any permutation \(\pi :[\kappa ] \longrightarrow [\kappa ]\) we have$$ \mathbf {e} ({{h}} _1,\ldots ,{{h}} _j {{{h}} '}_j,\ldots ,{{h}} _\kappa ) = \mathbf {e} ({{h}} _1,\ldots ,{{h}} _j,\ldots ,{{h}} _\kappa ) \mathbf {e} ({{h}} _1,\ldots ,{{h}} '_j,\ldots ,{{h}} _\kappa ). $$We refer to all the other cases as being asymmetric. To distinguish the target group we frequently write \({{\mathbb {G}}} _T\) instead of \({{\mathbb {G}}} _{\kappa +1}\) (and similarly for \({\mathsf {1}}_T\) and \( g _T\) in place of \({\mathsf {1}}_{\kappa +1}\) and \( g _{\kappa +1}\)) as its structure in our construction will be different from that of the source groups \({{\mathbb {G}}} _1,\ldots ,{{\mathbb {G}}} _{\kappa }\).$$ \mathbf {e} ({{h}} _{1},\ldots ,{{h}} _{\kappa }) = \mathbf {e} (h_{\pi (1)},\ldots ,{{h}} _{\pi (\kappa )}). $$

\(\mathbf {Sam} _i(z)\) : This is the sampling algorithm. On input \(z \in \mathbb {N}\) it outputs \({{h}} \in {{\mathbb {G}}} _i\) whose distribution is “close” to that of uniform over the equivalence class \({{\mathbb {G}}} _i( g _i^z)\). Here “close” is formalized via computational, statistical or perfect indistinguishability. We also allow a special input \(\varepsilon \) to this algorithm, in which case the sampler is required to output a uniformly distributed \({{h}} \in {{\mathbb {G}}} _i\) together with a z such that \({{h}} \in {{\mathbb {G}}} _i( g _i^z)\). When outputting z is not required, we say that \(\mathbf {Sam} _i(\varepsilon )\) is discretelogarithm oblivious. Note that for groups with unique encodings these algorithms trivially exist. For notational convenience, for a known a we define \({[a]}_i\) to be an element sampled via \(\mathbf {Sam} _i(a)\).
In some applications, we also rely on the following algorithm, which provides a canonical string for all group elements within an equivalence class.

\(\mathbf {Ext} _i({{h}})\) : This is the extraction algorithm. On input \({{h}} \in {{\mathbb {G}}} _i\) it outputs a string \(s \in \{0,1\}^{p(\lambda )}\) where \(p(\cdot )\) denotes a polynomial function. We demand that for any \({{h}} _1,{{h}} _2 \in {{\mathbb {G}}} _i\) with \({{h}} _1 = {{h}} _2\) in \({{\mathbb {G}}} _i\) we have that \(\mathbf {Ext} _i({{h}} _1)= \mathbf {Ext} _i({{h}} _2)\) (as bitstrings). We also require that the distribution of \(\mathbf {Ext} _i({[z]}_i)\) is uniform over \(\{0,1\}^{p(\lambda )}\), for \({[z]}_i {{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}\mathbf {Sam} _i(\varepsilon )\). For groups with unique encodings this algorithm trivially exists.
In the full version of the paper we provide possible extensions to this syntax.
Comparison with GGH. Our formalization differs from that of [GGH13a] which defines a graded encoding scheme. The main difference is that a graded encoding scheme defines a \(\mathbf {e} _{i,j}\) algorithm that takes inputs from \({{\mathbb {G}}} _i\) and \({{\mathbb {G}}} _j\) and returns an element in \({{\mathbb {G}}} _{i+j}\) such that the result is linear in each input. Moreover, the abstraction and construction of graded encodings schemes in [GGH13a] do not provide any validity algorithms; these are useful in certain adversarial situations such as CCA security and signature verification. Further, all known candidate constructions of graded encoding schemes are noisy and only permit a limited number of operations.
4 The Construction
We now present our construction of an MLG scheme \(\varGamma \) according to the syntax introduced in Sect. 3. In the later sections we will consider special cases of the construction and prove the hardness of analogues of the multilinear DDH problem under various assumptions.
We rely on the following building blocks in our MLG scheme. (1) A cyclic group \({{\mathbb {G}}} _0\) of some order \(N_0\) with generator \( g _0\) and identity \({\mathsf {1}}_0\); formally we think of this as a 1linear MLG scheme \(\varGamma _0\) with unique encodings in which \(\mathbf {e} \) is trivial; the algorithm \(\mathbf {Val} _0\) implies that elements of \({{\mathbb {G}}} _0\) are efficiently recognizable. (2) A generalpurpose obfuscator \({{\mathbf {Obf}}} \). (3) An additively homomorphic publickey encryption scheme \(\mathrm {\Pi }:=({{\mathbf {Gen}}},{{\mathbf {Enc}}},{{\mathbf {Dec}}},{{\mathbf {Eval}}})\) with plaintext space \(\mathbb {Z}_{N}\) (alternatively, a perfectly correct HPKE scheme). (4) A dualmode NIZK proof system. (5) A family \(\mathcal {TD}\) of (families of) languages \(\mathsf {TD}\)which has a hard subset membership problem, and such that all \(\mathsf {TD}\)have efficiently computable witness relations with unique witnesses.^{6} (See Sect. 2 for more formal definitions.)
We reserve variables and algorithms with index 0 for the base scheme \(\varGamma _0\); we also write \(N=N_0\). We require that the algorithms of \(\varGamma _0\) except for \(\mathbf {Setup} _0\) and \(\mathbf {Sam} _0\) are deterministic. We will also use the bracket notation to denote the group elements in \({{\mathbb {G}}} _0\). For example, we write \({[z]}_0,{[z']}_0 \in {{\mathbb {G}}} _0\) for two valid elements of the base group and \({[z]}_0+{[z']}_0 \in {{\mathbb {G}}} _0\) for \(\mathbf {Op} _0({[z]}_0,{[z']}_0)\). Variables with nonzero indices correspond to various source and target groups. Given all of the above components, our MLG scheme \(\varGamma \) consists of algorithms as detailed in the sections that follow.
4.1 Setup
4.2 Validity and Equality
The elements of \({{\mathbb {G}}} _i\) for \(1 \le i \le \kappa \) are tuples of the form \({{h}} = ({[z]}_0,{{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}},{{\pi }})\) where \({{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}} \) are encryptions of vectors from \(\mathbb {Z}_{N}^\ell \) under \(,{{ pk }} _1,{{ pk }} _2\), respectively (encryption algorithm \({{\mathbf {Enc}}} \) extends from plaintext space \(\mathbb {Z}_{N}\) to \(\mathbb {Z}_{N}^\ell \) in the obvious way) and where \({{\pi }} \) is a NIZK to be defined below. We refer to \(({{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}},{{\pi }})\) as the auxiliary information for \({[z]}_0\). The elements of \({{\mathbb {G}}} _{\kappa +1}\) are just those of \({{\mathbb {G}}} _0\).
Relation \({{\mathbf {R}}_{2}}\) depends on the language \(\mathsf {TD}\), and on input \({{ gpk }} \), tuple \(({[z]}_0,{{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}})\), and witness \(w_y\) accepts iff \( y \in \mathsf {TD}\).
For \(1 \le i \le \kappa \), the \(\mathbf {Val} _i\) algorithm for \(\varGamma \), on input \(({[z]}_0,{{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}},{{\pi }})\), first checks that the first component is in \({{\mathbb {G}}} _0\) using \(\mathbf {Val} _0\) and then checks the proof \({{\pi }} \); if both tests pass, it then returns \(\top \), else \(\bot \). Observe that for an honest choice of \({{ crs }} = ({{ crs }} ',y)\), the perfect completeness and the perfect soundness of the proof system ensure that only those elements which pass relation \({{\mathbf {R}}_{1}} \) are accepted. Algorithm \(\mathbf {Val} _{\kappa +1}\) just uses \(\mathbf {Val} _0\).
The equality algorithm \(\mathbf {Eq} _i\) of \(\varGamma \) for \(1 \le i \le \kappa \) first checks the validity of the two group elements passed to it and then returns true iff their first components match, according to \(\mathbf {Eq} _0\), the equality algorithm from the base scheme \(\varGamma _0\). Algorithm \(\mathbf {Eq} _{\kappa +1}\) just uses \(\mathbf {Eq} _0\). The correctness of this algorithm follows from the perfect completeness of \({{\mathrm {\Sigma }}} \).
4.3 Group Operations
We provide a procedure that, given as inputs \({{h}} =([ z ] _0, {{\mathbf {c}}_{1}},{{\mathbf {c}}_{2}},{{\pi }})\) and \({{h}} '=([ z' ] _0, {{\mathbf {c}}_{1}} ',{{\mathbf {c}}_{2}} ',{{\pi }} ') \in {{\mathbb {G}}} _i\), generates a tuple representing the product \(h\cdot h'\). This, in particular, will enable our multilinear map to be run on the additions of group elements whose explicit representations are not necessarily known. We exploit the structure of the base group as well as the homomorphic properties of the encryption scheme to “add together” the first three components. We then use \(({{ sk }_{1}},{{ sk }_{2}})\) as a witness to generate a proof \({{\pi }} ''\) that the new tuple is well formed. (For technical reasons we check the validity of \({{h}} \) and \({{h}} '\) in two different ways: using proofs \({{\pi }} \), \({{\pi }} '\), and also explicitly using \(({{ sk }_{1}},{{ sk }_{2}})\). Note that, although useful in the analysis, the explicit check is redundant by the perfect soundness of the proof system under a binding \({{ crs }} '\).)
4.4 The Multilinear Map
4.5 Sampling and Extraction
Since the target group has unique encodings, as noted in Sect. 3, an extraction algorithm for all groups can be derived from one for the target group. The latter can be implemented by applying a universal hash function to the group elements in \({{\mathbb {G}}} _T\), for example.
5 Indistinguishability of Encodings
In this section we will state two theorems that are essential tools in establishing the intractability of the \(\kappa \text {}\mathrm {MDDH} \) for our MLG scheme \(\varGamma \) constructed in Sect. 4. These theorems, roughly speaking, state that valid encodings of elements within a single equivalence class are computationally indistinguishable. We formalize this property via the \(\kappa \text {}\mathrm {Switch} \) game shown in Fig. 2. This game lets an adversary \(\mathcal {A} \) choose an element \([ z ] _i \in {{\mathbb {G}}} _i\) by producing two valid representations \(({{\mathbf {x}}} _{0},{{\mathbf {y}}} _{0})\) and \(({{\mathbf {x}}_{1}},{{\mathbf {y}}_{1}})\) for it. The adversary is given an encoding of \([ z ] _i\) generated using \(({{\mathbf {x}}_{b}},{{\mathbf {y}}_{b}})\) for a random b, and has to guess the bit b. In this game, besides access to \({{ pp }} \), which contains the obfuscated circuits for the group operation and the multilinear map, we also provide the matrix \({{\mathbf {W}}} \) in the clear to the adversary. This strengthens the \(\kappa \text {}\mathrm {Switch} \) game and is needed for our later analysis.
5.1 Using Probabilistic Indistinguishability Obfuscation
The indistinguishability of encodings using the first set of assumptions above is conceptually simpler to prove and we start with this case. Intuitively, the \(\mathrm {IND{\text {}}CPA} \) security of the encryption scheme will ensure that the encryptions of the two representations are indistinguishable. This argument, however, does not immediately work as the parameters \({{ pp }} \) contain component \(\overline{C}_\mathrm {Add}\) that depends on both decryption keys. We deal with this by finding an alternative implementation of this circuit without the knowledge of the secret keys, in the presence of a slightly different public parameters (which are computationally indistinguishable to those described in Sect. 4). The next lemma, roughly speaking, says that provided parameters \({{ pp }}\) include an instance \(y\in \mathsf {TD}\), then there exists an alternative implementation \(\widehat{C}_{\mathrm {Add}}\) that does not use the secret keys, and whose obfuscation is indistinguishable to that of \(C_{\mathrm {Add}}\) of Fig. 1 (top) for an adversary that knows the secret keys. It relies on the security of the obfuscator and the security of the NIZK proof system. A formal proof is in the full version, we give an overview of the proof below.
Lemma 1
Proof
(Sketch). The crucial observation is that a witness \(w_y\) to \(\widetilde{y}\in \mathsf {TD}\) is also a witness to \(x\in {{\mathbf {R}}} \), and therefore \(\widehat{C}_{\mathrm {Add}}\) can use \(w_y\) instead of \({{ sk }_{1}}\), \({{ sk }_{2}}\) to produce the output proof \({{\pi }} ''\). Below we provide brief descriptions of the transformation from \(C_{\mathrm {Add}}\) to \(\widehat{C}_{\mathrm {Add}}\), as well as some intuition for the justifications of each step.

\(\mathrm {Game} _0\): We start with (a \(\mathrm {PIO}\) obfuscation of) circuit \(C_{\mathrm {Add}}\) of Fig. 1 and with \(\widetilde{{{ pp }}}\) including \(\widetilde{y}\in \mathsf {TD}\) and a binding \({{ crs }} '\).

\(\mathrm {Game} _1\): The circuit has witness \(w_y\) to \(\widetilde{y}\in \mathsf {TD}\) hardcoded. If some input reaches the “invalid” branches (steps 5a or 5b of \(C_{\mathrm {Add}}\); see Fig. 1 (top)), \(C_{\mathrm {Add}}\) does not extract a witness from the corresponding proof, but instead uses \(w_y\) to generate proof \({{\pi }} ''\). Since the witness \(w_y\) is unique, and the CRS \({{ crs }} '\) guarantees perfect soundness, this leads to exactly the same behavior of \(C_{\mathrm {Add}}\) in Game 0. Hence, this hop is justified by \(\mathrm {PIO}\). Note that Game 1 requires no extraction trapdoor \({{ td }_{ext}} \) anymore.

\(\mathrm {Game} _2\): The CRS \(\widehat{{{ crs }}}'\) included in the public parameters is now hiding (such that the generated proofs are perfectly witnessindistinguishable).

\(\mathrm {Game} _3\): Here, output proofs \({{\pi }} ''\) for those inputs entering the “valid” branch (step 5c; see Fig. 1) use \(w_y\) (and not \({{ sk }} _1,{{ sk }} _2\)) as witness. In particular, this game does not need to perform a explicit validity check (using \({{ sk }} _1,{{ sk }} _2\)) anymore. This hop is justified by \(\mathrm {PIO}\), where the perfect witness indistinguishability of \(\widehat{{{ crs }}}'\) (when constructed as a hiding CRS) guarantees that the \(C_{\mathrm {Add}}\) circuits in Games 2 and 3 have identically distributed outputs.
With the above lemma we can invoke \(\mathrm {IND{\text {}}CPA} \) security, and via a sequence of games obtain the result stated below. The proof can be found in the full version; here we give a highlevel overview of the proof (see also Fig. 4).
Theorem 1
Proof
(Sketch). The strategy of the proof is as follows. We start replacing parameters \({{ pp }}\) as described in Sect. 4 with parameters \(\widetilde{pp}\) of Lemma 1, the latter include an instance \(\widetilde{y}\in \mathsf {TD}\), this hop is justified by the hardness of deciding membership in \(\mathsf {TD}\); then we apply Lemma 1 to replace parameters \(\widetilde{{{ pp }}}\) with \(\widehat{{{ pp }}}\), including an obfuscation of circuit \(\widehat{C}_{\mathrm {Add}}\) of Fig. 3; at this point we invoke the \(\mathrm {IND{\text {}}CPA} \) security of the encryption scheme to change the representation vector encrypted under \({{ pk }_{2}}\) of the challenge encoding (the challenge proof \({{\pi }} ^*\) is generated using simulator trapdoor \({{ td }_{zk}} \), and hence is identically distributed to a real proof); next, we revert back to parameters \({{ pp }}\), including a noinstance \(y\notin \mathsf {TD}\) and an obfuscation of circuit \(C_{\mathrm {Add}}\) of Fig. 1, which is justified again by the hardness of \(\mathsf {TD}\)and Lemma 1; note that now it is possible to use \({{ sk }_{2}}\) in \(C_{\mathrm {Map}}\), instead of \({{ sk }_{1}}\), invoking the security of \(\mathbf {PIO}\) (functional equivalence follows from the perfect soundness of the NIZK with a binding CRS); last, we repeat the same steps to change the representation vector encrypted under \({{ pk }_{1}}\). This completes the proof. (See Fig. 4 for a sketch of the hybrids.)
5.2 Doing Without Probabilistic Obfuscation
Again, we stress that Groth–Sahai proofs have the desired property (when restricting to statements with witnesses \(w\in \{0,1\}^*\) that are bit strings). We give more details in the full version of this paper.
The deterministic circuit \(C_{\mathrm {Add}}\). We now comment on a necessary slight tweak to the multilinear map construction itself. Namely, we have to view both \(C_{\mathrm {Add}}\) and \(C_{\mathrm {Map}}\) as deterministic circuits (so they can be obfuscated using an indistinguishability obfuscator \({{\mathbf {IO}}} \)). For \(C_{\mathrm {Map}}\), this is trivial, since it already is deterministic. Furthermore, we can view \(C_{\mathrm {Add}}\) as a deterministic circuit that takes as input (among other things) random coins r, and outputs (among other things) a NIZK proof \(\pi ={{\mathbf {Prove}}} ({{ gpk }},{{ crs }},x,w;r)\) for a fixed witness w hardwired into \(C_{\mathrm {Add}}\). For our purposes, we use a slight variation of \(C_{\mathrm {Add}}\) that instead generates \(\pi \) as \({{\mathbf {Prove}}} ({{ gpk }},{{ crs }},x,w;R)\), where R is a uniformly random value that is hardwired (upon creation time) into \(C_{\mathrm {Add}}\). When we want to make the choice of R explicit, we also write \(C_{\mathrm {Add}}^R\).
For this slight variation of our construction, we claim:
Theorem 2
Here, we only give a brief intuition for the proof. A more detailed proof is given in the full version.
In a nutshell, the proof of Theorem 2 proceeds like that of Theorem 1, except of course in those steps that use the security of the probabilistic indistinguishability obfuscator \(\mathbf {PIO} \). There are two types of such steps (resp. changes of \(C_{\mathrm {Map}}\) or \(C_{\mathrm {Add}}\)): in the first type, functional equivalence is fully preserved (even when viewing \(C_{\mathrm {Add}}\) as a deterministic circuit. This type of change occurs in the hop from Game\(_0\) to Game\(_1\) in the proof of Lemma 1, and in the hops from Game\(_5\) to Game\(_6\) and from Game\(_{11}\) to Game \(_{12}\) in the proof of Theorem 1. Since the corresponding deterministic circuits are functionally equivalent (in case of \(C_{\mathrm {Add}}=C_{\mathrm {Add}}^R\): when the same value of \(R\) is used), the security of \({{\mathbf {IO}}} \) can be directly utilized.
Hence, this change can be justified with a reduction to the (deterministic) indistinguishability property of \({{\mathbf {IO}}}\). Specifically, a suitable circuit sampler would sample circuits \(C_1:=C_{\mathrm {Add},1}^{R}\) and \(C_2:=C_{\mathrm {Add},2}^{R+\varDelta }\) for a uniform R, and a \(\varDelta \) generated from the corresponding witnesses. (We note that during this reduction, we can of course assume both relevant witnesses \(({{ sk }} _1,{{ sk }} _2)\) and \(w_y\) to be known.)
The remaining parts of the proof of Theorem 2 (including the proof of Lemma 1) apply unchanged.
6 The Multilinear DDH Problem
In the full version we show that natural multilinear analogues of the decisional Diffie–Hellman (DDH) problem are hard for our MLG scheme \(\varGamma \) from Sect. 4. We will establish this for two specific \(\mathbf {Setup} \) algorithms which give rise to symmetric and asymmetric multilinear maps in groups of prime order N. (See Sect. 3 for the formal definition.) In the symmetric case, we will base hardness on the qstrong DDH problem [BBS04] and in the asymmetric case on the standard DDH problem.
6.1 Intractable Problems
6.2 The Symmetric Setting
We describe a special variant of our general construction in Sect. 4 which gives rise to a symmetric MLG scheme as defined in Sect. 3. Recall that in the construction a matrix \({{\mathbf {W}}} \) was chosen uniformly at random in \(\mathbb {Z}_N^{\kappa \times \ell }\). We set \(\ell :=2\) and sample \({{\mathbf {W}}} = ({{\varvec{\omega }}} _1,\ldots ,{{\varvec{\omega }}} _\kappa )^t\) by setting \({{\varvec{\omega }}} _i = (1,\omega )\) for a random \(\omega \in \mathbb {Z}_N\). The generators and identity elements for all groups are set to be a single value generated for the first group. These modifications ensure that the scheme algorithms are independent of the index for \(1 \le i \le \kappa \) and that \(\mathbf {e} \) is invariant under all permutations of its inputs.
The following lemma, which provides a mechanism to compute polynomial values “in the exponent,” will be helpful in the security analysis of our constructions.
Lemma 2
(Horner in the exponent). Let \(\varvec{\omega } = (\omega _0,\omega _1,\omega _2) \in \mathbb {Z}_N\), and \({{\mathbf {x}}} _i = (x_{i,0}, x_{i,1},x_{i,2}) \in \mathbb {Z}_N^{3}\) for \(i=1\dots \kappa \). Define \(z_i := \langle {{\mathbf {x}}} _i,\varvec{\omega } \rangle \). Then given only the implicit values \([ \omega _0^i \omega _1^j \omega _2^k ] _T\), for all i, j, k such that \(i+j+k=\kappa \) and the explicit values \({{\mathbf {x}}} _i\) the element \([ z_1 \cdots z_n ] _T\) can be efficiently computed.
Proof
A formal statement and proof of the following result is in the full version of the paper, here we give a high level overview. Below \(I=I^*\) denotes the index set with all the second components being 1.
Theorem 3
Proof
(Sketch). In our reduction, the value \(\omega \) used to generate \({{\mathbf {W}}} \) will play the role of the implicit value in the \(\mathrm {SDDH} \) problem instance. We therefore change the implementation of \(C_\mathrm {Map}\) to one that does not know \(\omega \) in the clear and only uses the implicit values \([ \omega ^i ] _0\) (recall that in our construction \({{\mathbb {G}}} _T\) is just \({{\mathbb {G}}} _0\), so these elements come from the \(\mathrm {SDDH} \) instance). Such a circuit \(C^*_\mathrm {Map}\) can be efficiently implemented using Horner’s rule above. In more detail, \(C_\mathrm {Map}^*\) has \([ \omega ^i ] _T\) hardcoded in, recovers \({{\mathbf {x}}} _i\) from its inputs using \({{ sk }} _1\), and then applies Lemma 2 with \((\omega _0,\omega _1,\omega _2) := (1,\omega ,0)\) to evaluate the multilinear map.
The proof proceeds along a sequence of \(\kappa +6\) games as follows.

\(\mathrm {Game} _0\): This is the \(\kappa \text {}\mathrm {MDDH} \) problem (Fig. 5, right). We use \({{\mathbf {x}}_{i}} \) and \({{\mathbf {y}}_{i}} \) to denote the representation vectors of \(a_i\) generated within the sampler \(\mathbf {Sam} _{I(i)}(a_i)\), where \((i,I(i)) \in I\).

\(\mathrm {Game} _1\)–\(\mathrm {Game} _\kappa \): In these games we gradually switch the representations of \([a_i]_1\) for \(i \in [\kappa ]\) so that they are of the form \((a_i\omega ,1)\). Each hop can be bounded via the \(\mathrm {Switch} \) game. (We have not (yet) changed the representation of \([a_{\kappa +1}]_1\).)
 \(\mathrm {Game} _{\kappa +1}\): This game introduces a conceptual change: the \(a_i\) for \(i \in [\kappa ]\) are generated as \(a_i + \omega \). Note that the distributions of these values are still uniform and that the exponent of the \(\mathrm {MDDH} \) challenge when \(b=1\) isThis game prepares us for embedding a \((\kappa 1)\text {}\mathrm {SDDH} \) challenge and then to stepwise randomize the exponent above.$$ a_{\kappa +1} \cdot \prod _{i=1}^{\kappa } (a_i+\omega ). $$

\(\mathrm {Game} _{\kappa +2}\): This game switches \(C_\mathrm {Map}\) to \(C^*_\mathrm {Map}\) as defined above. We use indistinguishability obfuscation and the fact that these circuits are functionally equivalent to bound this hop. We are now in a setting where \(\omega \) is only implicitly known.

\(\mathrm {Game} _{\kappa +3}\): This game replaces \([\omega ^\kappa ]_0\) with a random value \([\tau ]_0\) in \(C^*_\mathrm {Map}\) and the computation of the challenge exponent. This hop can be bounded via the \((\kappa 1)\text {}\mathrm {SDDH} \) game. Note that at this point the exponent is not informationtheoretically randomized as \(\tau \) is used within \(C^*_\mathrm {Map}\).

\(\mathrm {Game} _{\kappa +4}\): This game sets the representation of \([a_{\kappa +1}]_1\) to \((a_{\kappa +1}\omega ,1)\). Once again, this hop can be bounded by the \(\mathrm {Switch} \) game.

\(\mathrm {Game} _{\kappa +5}\): This game introduces a conceptual change analogous to that in \(\mathrm {Game} _{\kappa +1}\) for \(a_{\kappa +1}\). Note that a linear factor \((a_{\kappa +1}+\omega )\) is introduced in this game. This will help to fully randomize the exponent next.

\(\mathrm {Game} _{\kappa +6}\): Analogously to \(\mathrm {Game} _{\kappa +3}\), this game replaces \([\omega ^\kappa ]_0\) with a random value \([\sigma ]_0\). We bound this hop using the \((\kappa 1)\text {}\mathrm {SDDH} \) game.
In \(\mathrm {Game} _{\kappa +6}\), irrespective of the value of \(b\in \{0,1\}\), the challenge is uniformly and independently distributed as \(\sigma \) remains outside the view of the adversary. Hence the advantage of any (unbounded) adversary in this game is 0. This concludes the sketch proof.
6.3 The Asymmetric Setting
We describe a second variant of the construction in Sect. 4 that results in an asymmetric MLG scheme. We set \(\ell :=2\) and choose the matrix \({{\mathbf {W}}} = ({{\varvec{\omega }}} _1,\ldots ,{{\varvec{\omega }}} _\kappa )^t\) by setting \({{\varvec{\omega }}} _i := (1,\omega _i)\) for random \(\omega _i \in \mathbb {Z}_N\).
The following theorem shows that for index set \(I = \{(i,I(i)):1 \le i \le \kappa + 1\}\) given by an arbitrary function \(I:[\kappa +1] \longrightarrow [\kappa ]\) of range at least 3, this construction is \((\kappa ,I)\text {}\mathrm {MDDH} \) intractable under the standard \(\mathrm {DDH} \) assumption in the base group, the security of the obfuscator, and the \(\kappa \text {}\mathrm {Switch} \) game in Sect. 5. We present the proof intuition here and leave the details to the full version.
Theorem 4
Proof
(Sketch). The general proof strategy is similar to that of the symmetric case, and proceeds along a sequence of 8 games as follows.

\(\mathrm {Game} _0\): This is the \((\kappa ,I)\text {}\mathrm {MDDH} \) problem. Without loss of generality we assume that \(I(i)=i\) for \(i\in [3]\).

\(\mathrm {Game} _1\)–\(\mathrm {Game} _3\): In these games we gradually switch the representation vectors of \([a_i]_i\) for \(i=1,2,3\) to those of the form \((a_i\omega _i,1)\). Each of these hops can be bounded via the \(\mathrm {Switch} \) game.
 \(\mathrm {Game} _4\): This game introduces a conceptual change and generates \(a_i\) as \(a_i + \omega _i\). The exponent of the \(\mathrm {MDDH} \) challenge when \(b=1\) is$$ (a_1 + \omega _1)(a_2+\omega _2)(a_3+\omega _3) \cdot \prod ^{\kappa +1}_{j \ge 4}a_j. $$

\(\mathrm {Game} _5\): In this game we change the implementation of \(C_\mathrm {Map}\) to one which uses all but two of the \(\omega _i\) explicitly, the remaining two implicitly, and additionally \([\omega _1\omega _2]_0\), i.e., \(\omega _1\omega _2\) given implicitly in the exponent. The new circuit \(C^*_\mathrm {Map}\) will be implemented using Horner’s rule and is functionally equivalent to the original circuit used in the scheme. We invoke the \(\mathrm {IO} \) security of the obfuscator to conclude the hop. This game prepares us to embed a \(\mathrm {DDH} \) challenge next.

\(\mathrm {Game} _6\): In this game we replace all the occurrences of \([\omega _1\omega _2]_0\) with a random \([\tau ]_0\) and the corresponding implicit values. We bound the distinguishing advantage in this hop down to the \(\mathrm {DDH} \) game.

\(\mathrm {Game} _7\): Similarly to \(\mathrm {Game} _5\), we change the implementation of \(C^*_\mathrm {Map}\) using \([\tau \omega _3]_0\) and argue via indistinguishability of obfuscations for functionally equivalent circuits.

\(\mathrm {Game} _8\): Finally, using the hardness of \(\mathrm {DDH} \), we replace all the occurrences of \([\tau \omega _3]_0\) with a random \([\sigma ]_0\).
In \(\mathrm {Game} _8\), irrespective of the value of \(b\in \{0,1\}\), the challenge is uniformly and independently distributed as \(\sigma \) remains outside the view of the adversary. Hence the advantage of any (possibly unbounded) adversary in this game is 0.
7 The Rank Problem
The \(\mathrm {RANK} \) problem is a generalization of \(\mathrm {DDH} \)like problems to matrices and has proven to be very useful in cryptographic constructions [BHHO08, NS09, GHV12, BLMR13, EHK+13]. Here we consider the problem in groups with nonunique encodings equipped with a multilinear map. Our main result is to show that, subject to certain restrictions, the intractability of the rank problem for our construction of an MLG scheme \(\varGamma \) from Sect. 4 follows from that of the \(q\text {}\mathrm {SDDH} \) problem for \(\varGamma _0\).
7.1 Formalization of the Problem
7.2 The \(\mathrm {RANK}\) Problem with Our MLG Scheme
Let \({{ pp }} \) denote the public parameters of such an MLG scheme, obtained by running \(\mathbf {Setup} \) with input \((1^\lambda ,1^\kappa )\). For simplicity, we focus on the case where N is prime. Let \({{\mathrm {Rk}}} _{r}(\mathbb {Z}_N^{m \times n})\) denote the set of \(m \times n\) matrices over \(\mathbb {Z}_N\) of rank r, where necessarily \(r \le \min (m,n)\). We use a variant of our construction in Sect. 4, setting \(\ell :=3\) and sampling \({{\mathbf {W}}} = ({{\varvec{\omega }}} _1,\ldots ,{{\varvec{\omega }}} _\kappa )^t \in \mathbb {Z}_N^{\kappa \times 3}\) where \({{\varvec{\omega }}} _i = (1,\omega ,\omega ^2)\) for \(\omega {{\mathrm{{\leftarrow \!\!{\tiny {\$}\normalsize }}\,}}}\mathbb {Z}_N\). Note that this results in a symmetric pairing and henceforth we omit subscripts from source group elements. Let \([ {{\mathbf {M}}} ] \) denote a matrix whose (i, j)th entry contains an encoding of the form \([ m_{i,j} ] = ([ m_{i,j} ] _0,{{\mathbf {c}}_{i,j,1}},{{\mathbf {c}}_{i,j,2}},\pi _{i,j})\), with \(m_{i,j} \in \mathbb {Z}_N\).
We show that for our construction in Sect. 4, with the modification introduced above, the rank problem is indeed hard provided \(\kappa \le r_0 < r_1\). A standard hybrid argument shows that it is sufficient to establish this for \(r_1 := r_0 + 1\), with a polynomial loss in the security. Our main result is stated below. The proof is in the full version of the paper, here we give only give some intuition.
Theorem 5
7.3 Proof Intuition
The main difficulty comes in generating consistent encodings of a rank r challenge matrix \([ {{\mathbf {M}}} ] \) throughout its gradual transformation into a rank \(r+1\) challenge matrix. Contrast this with the \(\mathrm {MDDH}\) reduction of Sect. 6, where the challenge that is transformed lives in the target group —a group with unique encodings. As we will see below, having encodings that are represented also with respect to \(\omega ^2\) will help to overcome this problem and embed a \(1\text {}\mathrm {SDDH} \) tuple.
Footnotes
 1.
This is not trivial since the new method should not lead to an exponential blowup in \(\kappa \).
 2.
The authors of [YYHK14] state that such information can be added in their construction, but what would be needed is the obfuscation of a circuit for computing 4xyth powers. The information available for building this would be obfuscations of circuits for computing 2xth and 2yth powers, so an obfuscation of a composition of already obfuscated circuits would be required. Strictly speaking then, the auxiliary information associated with elements output by their pairing is of a different type to that belonging to the inputs, making it questionable whether “selfpairing” is the right description of what is constructed in [YYHK14].
 3.
We note that extraction in Groth–Sahai proofs does not for all types of statements recover a witness. (Instead, for some types of statements, only \(g^{w_i}\) for a witness variable \(w_i\in \mathbb {Z}_p\) can be recovered.) Here, however, we will only be interested in witnesses \(w=(w_1,\dots ,w_n)\in \{0,1\}^{n}\) that are bit strings, in which case extraction always recovers \(w\). (Specifically, extraction will recover \(g^{w_i}\) for all \(i\), and thus all \(w_i\).).
 4.
We assume, without loss of generality, that all algorithms return \(\bot \) when run on invalid group elements.
 5.
However, note that \(N_i\) need not be the least integer with this property.
 6.
An example of such a language is the Diffie–Hellman language \(\mathsf {TD}=\{(g_1^r,g_2^r)\;\;r\in \mathbb {N}\}\) in a DDH group.
 7.
Typically, the obfuscated circuit will have a PRF key hardwired in and derives the required randomness by applying the PRF to the circuit inputs.
Notes
Acknowledgements
Albrecht, Larraia and Paterson were supported by EPSRC grant EP/L018543/1. Hofheinz was supported by DFG grants HO 4534/22 and HO 4534/41.
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