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Obfuscation from Low Noise Multilinear Maps

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Progress in Cryptology – INDOCRYPT 2018 (INDOCRYPT 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11356))

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Abstract

Multilinear maps enable homomorphic computation on encoded values and a public procedure to check if the computation on the encoded values results in a zero. Encodings in known candidate constructions of multilinear maps have a (growing) noise component, which is crucial for security. For example, noise in GGH13 multilinear maps grows with the number of levels that need to be supported and must remain below the maximal noise supported by the multilinear map for correctness. A smaller maximal noise, which must be supported, is desirable both for reasons of security and efficiency.

In this work, we put forward new candidate constructions of obfuscation for which the maximal supported noise is polynomial (in the security parameter). Our constructions are obtained by instantiating a modification of Lin’s obfuscation construction (EUROCRYPT 2016) with composite order variants of the GGH13 multilinear maps. For these schemes, we show that the maximal supported noise only needs to grow polynomially in the security parameter. We prove the security of these constructions in the weak multilinear map model that captures all known vulnerabilities of GGH13 maps. Finally, we investigate the security of the considered composite order variants of GGH13 multilinear maps from a cryptanalytic standpoint.

Research supported in part from DARPA/ARL SAFEWARE Award W911NF15C0210, AFOSR Award FA9550-15-1-0274, AFOSR YIP Award, DARPA and SPAWAR under contract N66001-15-C-4065, a Hellman Award and research grants by the Okawa Foundation, Visa Inc., and Center for Long-Term Cybersecurity (CLTC, UC Berkeley). The views expressed are those of the author and do not reflect the official policy or position of the funding agencies.

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Notes

  1. 1.

    Throughout this paper, we use multilinear maps to refer to private encoding multilinear maps. In other words, no public low-level encodings of zero are provided in our constructions.

  2. 2.

    By “fresh” encodings we mean that it is generated via the encoding procedure using the secret parameters and not produced as a result of homomorphic computations.

  3. 3.

    The reported noise is for the recommended version of the GGH multilinear maps [24, Sect. 6.4]. This recommendation was made in [25] with the goal of avoiding averaging attacks [20, 33, 45]. Similar recommendation is made in [3, Sect. 4.2].

  4. 4.

    Another exception is [37] which uses Reniy divergence to construct a map called GGHLite that supports more efficient concrete parameters than GGH.

  5. 5.

    Specifically, the subfield lattice attack is sub-exponential as soon as q is super-polynomial. Furthermore, using attack of [35] becomes polynomial for power-of-two cyclotomic fields when \(q = 2^{\varOmega (\sqrt{n \log \log n})}\). We note that the attack of [35] is much more general, but we are only concerned with these parameter choices.

  6. 6.

    In the first draft of [24], authors suggested a composite order variant of multilinear maps. However, in later versions they restricted their claims to the prime order construction. This was in light of the weak-discrete log attacks they found against their construction. However, these attacks worked only when public encodings of zero are provided and rendered assumptions such as subgroup hiding easy. In particular, all known attacks against composite order GGH maps use low level encodings of zero [25] or some specific high-level encodings of zero [15]. In light of the Miles et al. attacks [44] we envision more (potential) attacks but they are all captured by the weak multilinear map model.

  7. 7.

    We do not provide public encodings of zero in our constructions. Therefore, they are insufficient to instantiate the assumptions made by Gentry et al. [29, 30].

  8. 8.

    In the actual construction the structure of the elements of \(\mathbb {U}\) are much involved. But for simplicity here we just assume \(\mathbb {U}= [\ell ]\) that suffices to convey the main idea.

  9. 9.

    We use the notation \([\cdot ]_q\) to denote operations in \(R_q\).

  10. 10.

    Note that in the actual construction we use different restriction for multiplication due to difference in the structure of the straddling levels and the universe.

  11. 11.

    Notice that \(\varvec{g}/\varvec{z}_\mathbf{v }\) is in \({K}\). We generally use \(\varvec{{a}}/\varvec{{b}}\in {K}\) to denote “division” in the quotient field \({K}\) of \(R\) for \(\varvec{{a}},\varvec{{b}}\in R\). This is not to be confused with the notation \(\varvec{{a}}\cdot [\varvec{{b}}^{-1}]_q\in R\) which is a multiplication operation in \(R\) where the inverse \([\varvec{{b}}^{-1}]_q\) is in \(R_q\).

  12. 12.

    Notice that, the inverse is in \(R_q\) but the product is in \(R\).

  13. 13.

    There are some works e.g. [7, 11] that prove security of their constructions in slightly stronger models than the ideal graded encoding model which captures some attacks on multilinear maps.

  14. 14.

    \(\mathcal {C}^{\mathsf {PRF}_\psi }\) is a circuit for computing PRF with the key \(\psi \).

  15. 15.

    In the construction this is implemented by canceling out the PRF value by multiplying with an appropriate encoding that encodes a value which is \(0\,\mathsf {mod}\,\varvec{g}_2\) in the second slot.

  16. 16.

    We note that such a PRF can be computed using constant input types and constant type degree. See more details in Appendix G.2 of the full version [19].

  17. 17.

    The values of \(\mathbf e ^{t}\) is specified in the proof of Theorem G.20 of the full version [19], which is crucial for proving post zeroizing security, but does not affect the correctness of the obfuscator.

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Authors and Affiliations

  1. Center of IT-Security, Privacy and Accountability, Saarbrücken, Germany

    Nico Döttling

  2. University of California, Berkeley, USA

    Sanjam Garg & Peihan Miao

  3. Microsoft Research India, Bengaluru, India

    Divya Gupta

  4. Visa Research, Palo Alto, USA

    Pratyay Mukherjee

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  1. Nico Döttling
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  1. Indian Statistical Institute, Kolkata, India

    Debrup Chakraborty

  2. Nagoya University, Nagoya, Japan

    Tetsu Iwata

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Döttling, N., Garg, S., Gupta, D., Miao, P., Mukherjee, P. (2018). Obfuscation from Low Noise Multilinear Maps. In: Chakraborty, D., Iwata, T. (eds) Progress in Cryptology – INDOCRYPT 2018. INDOCRYPT 2018. Lecture Notes in Computer Science(), vol 11356. Springer, Cham. https://doi.org/10.1007/978-3-030-05378-9_18

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