Abstract
Non-interactive zero-knowledge (\(\mathsf {NIZK}\)) is a fundamental primitive that is widely used in the construction of cryptographic schemes and protocols. Despite this, general purpose constructions of \(\mathsf {NIZK}\) proof systems are only known under a rather limited set of assumptions that are either number-theoretic (and can be broken by a quantum computer) or are not sufficiently well understood, such as obfuscation. Thus, a basic question that has drawn much attention is whether it is possible to construct general-purpose \(\mathsf {NIZK}\) proof systems based on the learning with errors (\(\mathsf {LWE}\)) assumption.
Our main result is a reduction from constructing \(\mathsf {NIZK}\) proof systems for all of \(\mathbf {NP}\) based on \(\mathsf {LWE}\), to constructing a \(\mathsf {NIZK}\) proof system for a particular computational problem on lattices, namely a decisional variant of the Bounded Distance Decoding (\(\mathsf {BDD}\)) problem. That is, we show that assuming \(\mathsf {LWE}\), every language \(L \in \mathbf {NP}\) has a \(\mathsf {NIZK}\) proof system if (and only if) the decisional \(\mathsf {BDD}\) problem has a \(\mathsf {NIZK}\) proof system. This (almost) confirms a conjecture of Peikert and Vaikuntanathan (CRYPTO, 2008).
To construct our \(\mathsf {NIZK}\) proof system, we introduce a new notion that we call prover-assisted oblivious ciphertext sampling (\(\mathsf {POCS}\)), which we believe to be of independent interest. This notion extends the idea of oblivious ciphertext sampling, which allows one to sample ciphertexts without knowing the underlying plaintext. Specifically, we augment the oblivious ciphertext sampler with access to an (untrusted) prover to help it accomplish this task. We show that the existence of encryption schemes with a \(\mathsf {POCS}\) procedure, as well as some additional natural requirements, suffices for obtaining \(\mathsf {NIZK}\) proofs for \(\mathbf {NP}\). We further show that such encryption schemes can be instantiated based on \(\mathsf {LWE}\), assuming the existence of a \(\mathsf {NIZK}\) proof system for the decisional \(\mathsf {BDD}\) problem.
R. D. Rothblum—This research was conducted in part while the author was at MIT and Northeastern University. Research supported in part by the Israeli Science Foundation (Grant No. 1262/18). Research also supported in part by NSF Grants CNS-1413920 and CNS-1350619, by the Defense Advanced Research Projects Agency (DARPA) and the U.S. Army Research Office under contracts W911NF-15-C-0226 and W911NF-15-C-0236, the Simons Investigator award agreement dated 6-5-12 and the Cybersecurity and Privacy Institute at Northeastern University.
A. Sealfon—Research supported in part by a DOE CSGF fellowship, NSF MACS CNS-1413920, DARPA/NJIT Palisade 491512803, Sloan/NJIT 996698, MIT/IBM W1771646, NSF Center for Science of Information (CSoI) CCF-0939370, and the Simons Investigator award agreement dated 6-5-12.
K. Sotiraki—Research supported in part by NSF grants CNS-1350619, CNS-1718161, CNS-1414119.
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Notes
- 1.
As a matter of fact, resolving this question carries a symbolic cash prize; see https://simons.berkeley.edu/crypto2015/open-problems.
- 2.
- 3.
In particular, the naive algorithm that chooses at random \(b \in \{0,1\}\) and outputs \(E_{\mathsf {pk}}(b)\) is not oblivious since its random coins fully reveal b.
- 4.
For simplicity, we focus for now on schemes with perfect correctness.
- 5.
Further related issues were recently uncovered by Canetti and Lichtenberg [CL17].
- 6.
- 7.
Actually, it is important for us to also establish that \(\mathbf {{s}}\) is unique. We enforce this by having the matrix \(\mathbf {A}\) be specified as part of the CRS (rather than by the prover). Indeed, it is not too difficult to show that a lattice spanned by a random matrix \(\mathbf {A}\) does not have short vectors and therefore \(\mathbf {{b}}\) cannot be close to two different lattice points.
- 8.
In the literature, typically \(\mathbf {B}\) is defined as a set of column vectors. However, for our applications it is more convenient to use row vectors.
- 9.
Note that in the actual definition we only require the latter to hold with high probability over the choice of the public randomness for every valid public key. The notion of encryption schemes with public randomness is discussed in Sect. 2.1.
- 10.
- 11.
Here we are utilizing the fact that the hidden-bits proof-system has perfect completeness to save us the effort of arguing that the hidden bits are indeed (sufficiently) unbiased.
- 12.
The argument here resembles the standard argument for obtaining adaptively sound \(\mathsf {NIZK}\)s from \(\mathsf {NIZK}\)s that only have non-adaptive soundness.
- 13.
From Lemma 3 this happens with overwhelming probability.
- 14.
Since the complementary event happens with negligible probability in \(\kappa \), in case it does happen we choose the public-keys to have zero noise.
- 15.
Again, the complementary event happens with negligible probability, in which case we can output a ciphertext with zero noise.
- 16.
Alternatively, we could reduce the bias to be negligible using Von Neumann’s trick [VN61] for transforming a biased source to an almost unbiased source.
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Rothblum, R.D., Sealfon, A., Sotiraki, K. (2019). Towards Non-Interactive Zero-Knowledge for NP from LWE. In: Lin, D., Sako, K. (eds) Public-Key Cryptography – PKC 2019. PKC 2019. Lecture Notes in Computer Science(), vol 11443. Springer, Cham. https://doi.org/10.1007/978-3-030-17259-6_16
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