International Association
for Cryptologic Research

We introduce non-interactive distributionally indistinguishable arguments (NIDI) to address a significant weakness of NIWI proofs: namely, the lack of meaningful secrecy when proving statements about $\mathsf{NP}$ languages with unique witnesses.

NIDI arguments allow a prover P to send a single message to verifier V, given which V obtains a sample d from a (secret) distribution D, together with a proof of membership of d in an NP language L. The soundness guarantee is that if the sample d obtained by the verifier V is not in L, then V outputs $\bot$. The privacy guarantee is that secrets about the distribution remain hidden: for every pair of distributions $D_0$ and $D_1$ of instance-witness pairs in L such that instances sampled according to $D_0$ or $D_1$ are (sufficiently) hard-to-distinguish, a NIDI that outputs instances according to $D_0$ with proofs of membership in L is indistinguishable from one that outputs instances according to $D_1$ with proofs of membership in L.

- We build NIDI arguments for sufficiently hard-to-distinguish distributions assuming sub-exponential indistinguishability obfuscation and sub-exponential one-way functions.

- We demonstrate preliminary applications of NIDI and of our techniques to obtaining the first (relaxed) non-interactive constructions in the plain model, from well-founded assumptions, of:

1. Commit-and-prove that provably hides the committed message

2. CCA-secure commitments against non-uniform adversaries.

The commit phase of our commitment schemes consists of a single message from the committer to the receiver, followed by a randomized output by the receiver (that need not necessarily be returned to the committer).

We investigate the communication complexity of Byzantine agreement protocols for long messages against an adaptive adversary. In this setting, prior results either achieved a communication complexity of $O(nl\cdot\poly(\kappa))$ or $O(nl + n^2 \cdot \poly(\kappa))$ for $l$-bit long messages. We improve the state of the art by presenting protocols with communication complexity $O(nl + n \cdot \poly(\kappa))$ in both the synchronous and asynchronous communication models. The synchronous protocol tolerates $t \le (1-\epsilon) \frac{n}{2}$ corruptions and assumes a VRF setup, while the asynchronous protocol tolerates $t \le (1-\epsilon) \frac{n}{3}$ corruptions under further cryptographic assumptions. Our protocols are very simple and combine subcommittee election with the recent approach of Nayak et al. (DISC `20). Surprisingly, the analysis of our protocols is \emph{all but simple} and involves an interesting new application of Mc Diarmid's inequality to obtain {\em optimal} corruption thresholds.

First posed as a challenge in 1978 by Rivest et al., fully homomorphic encryption—the ability to evaluate any function over encrypted data— was only solved in 2009 in a breakthrough result by Gentry. After a decade of intense research, practical solutions have emerged and are being pushed for standardization.

This guide is intended to practitioners. It explains the inner-workings of TFHE, a torus-based fully homomorphic encryption scheme. More exactly, it describes its implementation on a discretized version of the torus. It also explains in detail the technique of the programmable bootstrapping.

Payment channels effectively move the transaction load off-chain thereby successfully addressing the inherent scalability problem most cryptocurrencies face. A major drawback of payment channels is the need to ``top up'' funds on-chain when a channel is depleted. Rebalancing was proposed to alleviate this issue, where parties with depleting channels move their funds along a cycle to replenish their channels off-chain. Protocols for rebalancing so far either introduce local solutions or compromise privacy.

In this work, we present an opt-in rebalancing protocol that is both private and globally optimal, meaning our protocol maximizes the total amount of rebalanced funds. We study rebalancing from the framework of linear programming. To obtain full privacy guarantees, we leverage multi-party computation in solving the linear program, which is executed by selected participants to maintain efficiency. Finally, we efficiently decompose the rebalancing solution into incentive-compatible cycles which conserve user balances when executed atomically.

The linear layer, which is basically a binary non-singular matrix, is an integral part of cipher construction in a lot of private key ciphers. As a result, optimising the linear layer for device implementation has been an important research direction for about two decades. The Boyar-Peralta's algorithm (SEA'10) is one such common algorithm, which offers significant improvement compared to the straightforward implementation. This algorithm only returns implementation with XOR2 gates, and is deterministic. Over the last couple of years, some improvements over this algorithm has been proposed, so as to make support for XOR3 gates as well as make it randomised. In this work, we take an already existing improvement (Tan and Peyrin, TCHES'20) that allows randomised execution and extend it to support three input XOR gates. This complements the other work done in this direction (Banik et al., IWSEC'19) that also supports XOR3 gates with randomised execution. Further, noting from another work (Maximov, Eprint'19), we include one additional tie-breaker condition in the original Boyar-Peralta's algorithm. Our work thus collates and extends the state-of-the-art, at the same time offers a simpler interface. We show several results that improve from the lastly best-known results.

Let $p$ be a polynomial, and let $p^{(i)}(x)$ be the result of iterating the polynomial $i$ times, starting at an input $x$. The case where $p(x)$ is the homogeneous polynomial $x^2$ has been extensively studied in cryptography. Due to its associated group structure, iterating this polynomial gives rise to a number of interesting cryptographic applications such as time-lock puzzles and verifiable delay functions. On the other hand, the associated group structure leads to quantum attacks on the applications.

In this work, we consider whether inhomogeneous polynomials, such as $2x^2+3x+1$, can have useful cryptographic applications. We focus on the case of polynomials mod $2^n$, due to some useful mathematical properties. The natural group structure no longer exists, so the quantum attacks but also applications no longer immediately apply. We nevertheless show classical polynomial-time attacks on analogs of hard problems from the homogeneous setting. We conclude by proposing new computational assumptions relating to these inhomogeneous polynomials, with cryptographic applications.

Most existing work on secure multi-party computation (MPC) ignores a key idiosyncrasy of modern communication networks, that there are a limited number of communication paths between any two nodes, many of whom might even be corrupted. The work by Garay and Ostrovsky [EUROCRYPT'08] on almost-everywhere MPC (AE-MPC), introduced “best-possible security” properties for MPC over such incomplete networks, where necessarily some of the honest parties may be excluded from the computation—we call such parties “doomed.”

In this work we provide a universally composable definition of almost-everywhere security, which allows us to automatically and accurately capture the guarantees of AE-MPC (as well as AE-communication, the analogous “best-possible security” version of secure communication) in the Universal Composability (UC) framework of Canetti. Our result offers the first simulation-based treatment of this important but under-investigated problem, along with the first simulation-based proof of AE-MPC.

Non-interactive publicly verifiable secret sharing (PVSS) schemes allow parties to re-share a secret in a decentralized setting in the presence of malicious parties. A recently proposed application of PVSS schemes is to enable permissionless proof-of-stake blockchains to ``keep a secret" via a sequence of committees that share that secret. Such committees can use the secret to produce signatures on the blockchain's behalf, or to disclose hidden data conditioned on consensus that some event has occurred. Such a setting may involve thousands of parties, so the PVSS scheme that it uses must be very efficient, both in computation and communication. Yet, previous PVSS schemes have large proofs and/or require many exponentiations over large groups.

We present a non-interactive PVSS scheme in which the underlying encryption scheme is based on the learning with errors (LWE) problem. While lattice-based encryption schemes are very fast, they have issues with bandwidth (long ciphertexts and public keys). We deal with the bandwidth issue in two ways. First, we adapt the Peikert-Vaikuntanathan-Waters (PVW) encryption scheme to the multi-receiver setting so that the bulk of the parties' keys is a common random string, and so that we get good amortized communication: $\Omega(1)$ plaintext/ciphertext rate (rate $\approx 1/60$ for 100 parties, $\approx 1/8$ for 1000 parties, approaching 1/2 as the number of parties grows). Second, we use bulletproofs over a DL-group of order about 256 bits to get compact proofs of correct encryption of shares. Switching from the lattice setting to the DL setting is relatively painless, as we equate the LWE modulus with the order of the group, and apply dimension reduction to vectors before the switch to minimize the number of exponentiations in the bulletproof. An implementation of our PVSS for 1000 parties showed that it's quite practical, and should remain so with up to a two order of magnitude increase in the group size.

Software implementations of the number-theoretic transform (NTT) method often leverage Harvey’s butterfly to gain speedups. This is the case in cryptographic libraries such as IBM’s HElib, Microsoft’s SEAL, and Intel’s HEXL, which provide optimized implementations of fully homomorphic encryption schemes or their primitives. We extend the Harvey butterfly to the radix-4 case for primes in the range [2^31, 2^52). This enables us to use the vector multiply sum logical (VMSL) instruction, which is available on recent IBM Z^(R) platforms. On an IBM z14 system, our implementation performs more than 2.5x faster than the scalar implementation of SEAL we converted to native C. In addition, we implemented a mixed-radix implementation that uses AVX512-IFMA on Intel’s Ice Lake processor, which happens to be ~1.1 times faster than the super-optimized implementation of Intel’s HEXL. Finally, we compare the performance of some of our implementation using GCC versus Clang compilers and discuss the results.

Homomorphic secret sharing (HSS) for a function $f$ allows input parties to distribute shares for their private inputs and then locally compute output shares from which the value of $f$ is recovered. HSS can be directly used to obtain a two-round multiparty computation (MPC) protocol for possibly non-threshold adversary structures whose communication complexity is independent of the size of $f$. In this paper, we propose two constructions of HSS schemes supporting parallel evaluation of a single low-degree polynomial and tolerating multipartite and general adversary structures. Our multipartite scheme tolerates a wider class of adversary structures than the previous multipartite one in the particular case of a single evaluation and has exponentially smaller share size than the general construction. While restricting the range of tolerable adversary structures (but still applicable to non-threshold ones), our schemes perform $\ell$ parallel evaluations with communication complexity approximately $\ell/\log\ell$ times smaller than simply using $\ell$ independent instances. We also formalize two classes of adversary structures taking into account real-world situations to which the previous threshold schemes are inapplicable. Our schemes then perform $O(m)$ parallel evaluations with almost the same communication cost as a single evaluation, where $m$ is the number of parties.

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The importance of efficient multi-exponen- tiation algorithms in a large spectrum of cryptographic applications continues to grow. Many of the algorithms proposed in the past pay attention exclusively on the minimization of the number of modular multiplications. However, a short reduction of the multiplicative com- plexity can be easily overshadowed by other figures of merit. In this article we demonstrate a large number of practical results aimed at concrete cryptographic tasks requiring multi-exponentiations and provide rec- ommendations on the best possible algorithmic strate- gies for different selection of security parameters.

Bulletproofs (Bünz et al. IEEE S&P 2018) are a celebrated ZK proof system that allows for short and efficient proofs, and have been implemented and deployed in several real-world systems. In practice, they are most often implemented in their non-interactive version obtained using the Fiat-Shamir transform, despite the lack of a formal proof of security for this setting.

Prior to this work, there was no evidence that malleability attacks were not possible against Fiat-Shamir Bulletproofs. Malleability attacks can lead to very severe vulnerabilities, as they allow an adversary to forge proofs re-using or modifying parts of the proofs provided by the honest parties. In this paper, we show for the first time that Bulletproofs (or any other similar multi-round proof system satisfying some form of weak unique response property) achieve simulation-extractability in the algebraic group model.

This implies that Fiat-Shamir Bulletproofs are non-malleable.

Block cipher DEFAULT has been proposed as a differential fault analysis immune cipher at Asiacrypt 2021. In this paper, we show that one can find the key of the initial version of DEFAULT with complexity $2^{16}$ by injecting 112 faults. However, our idea does not work in the modified version of the cipher.

In a recent talk of Hallgren on a joint work with Eldar (Sept 21, 2021, Simons Institute), a polynomial-time quantum algorithm for solving BDD in a certain class of lattices was claimed. We show here that known classical (and even, deterministic) polynomial-time algorithms already achieve this result.

Branching program (BP) is a DAG-based non-uniform computational model for L/poly class. It has been widely used in formal verification, logic synthesis, and data analysis. As a special BP, a decision tree is a popular machine learning classifier for its effectiveness and simplicity. In this work, we propose a UC-secure efficient multi-party computation platform for outsourced branching program and/or decision tree evaluation. We construct a constant-round protocol and a poly-round protocol. In particular, the overall (online + offline) communication cost of our poly-round protocol is $O(d(\ell + \log m+\log n))$ and its round complexity is $2d-1$, where $m$ is the DAG size, $n$ is the number of features, $\ell$ is the feature length, and $d$ is the longest path length. To enable efficient oblivious hopping among the DAG nodes, we propose a lightweight $1$-out-of-$N$ shared OT protocol with logarithmic communication in both online and offline phase. This partial result may be of independent interest to some other cryptographic protocols. Our benchmark shows, compared with the state-of-the-arts, the proposed constant-round protocol is up to 10X faster in the WAN setting, while the proposed poly-round protocol is up to 15X faster in the LAN setting.

Dot-product is a widely used operation in many machine learning and scientific computing algorithms. Recently, NVIDIA has introduced dot-product instructions (DP2A and DP4A) in modern GPU architectures, with the aim of accelerating machine learning and scientific computing applications. These dot-product instructions allow the computation of multiply-and-add instructions in a clock cycle, effectively achieving higher throughput compared to conventional 32-bit integer units. In this paper, we show that the dot-product instruction can also be used to accelerate matrix-multiplication and polynomial convolution operations, which are commonly found in post-quantum lattice-based cryptographic schemes. In particular, we propose a highly optimized implementation of FrodoKEM, wherein the matrix-multiplication is accelerated by the dot-product instruction. We also present specially designed data structures that allow an efficient implementation of Saber key encapsulation mechanism, utilizing the dot-product instruction to speed-up the polynomial convolution. The proposed FrodoKEM implementation achieves 4.37x higher throughput in terms of key exchange operations per second than the state-of-the-art implementation on V100 GPU. This paper also presents the first implementation of Saber on GPU platforms, achieving 124,418, 120,463, and 31,658 key exchange operations per second on RTX3080, V100, and T4 GPUs, respectively. Since matrix-multiplication and polynomial convolution operations are the most time-consuming operations in lattice-based cryptographic schemes, our proposed techniques are likely to benefit other similar algorithms. The proposed high throughput implementation of KEMs on various GPU platforms allows the heavy computations (KEMs) to be offloaded from the server. This is very useful for many emerging applications like Internet of Things and cloud computing.

Mixed integer linear programming (MILP) based tools are used to estimate the strength of block ciphers against the cryptanalytic attacks. The existing tools use partial difference distribution table (p-DDT) approach to optimize the probability of differential characteristics for large (≥8-bit) S-box based ciphers. We propose to use the full difference distribution table (DDT) with the probability of each possible propagation for MILP modeling of large S-boxes. This requires more than 16 variables to represent the linear inequalities of each propagation and corresponding probabilities. The existing tools (viz. Logic Friday) cannot handle the linear inequalities in more than 16 variables. In this paper, we present a new tool (namely MILES) to minimize the linear inequalities in more than 16 variables. This tool reduces the number of inequalities by minimizing the truth table corresponding to the DDT of S-box. We use our tool to minimize the linear inequalities for 8-bit S-boxes (AES and SKINNY) and get better results than existing tools. We show the application of MILES on 8-bit S-box based lightweight block cipher PIPO. There are 20621 inequalities in 23 variables corresponding to the possible propagations in DDT and these are minimized to 6035 inequalities using MILES. MILP model based on these linear inequalities is used to optimizethe probability of differential characteristics for round-reduced PIPO. For the first time, the MILP problem consisting the inequalities of full DDT for 8-bit S-box is solved to optimize the probability of differential characteristics.

We define the class of triplicate functions as a generalization of 3-to-1 functions over the finite field F 2 n for even values of n. We investigate the properties and behavior of triplicate functions, and of 3-to-1 among triplicate functions, with particular attention to the conditions under which such functions can be APN. We compute the exact number of distinct differential sets of power APN functions, quadratic 3-to-1 functions, and quadratic APN permutations; we show that, in this sense, quadratic 3-to-1 functions are a generalization of quadratic power APN functions for even dimensions, while quadratic APN permutations are generalizations of quadratic power APN functions for odd dimensions. We survey all known infinite families of APN functions with respect to the presence of 3-to-1 functions among them, and conclude that for even n almost all of the known infinite families contain functions that are quadratic 3-to-1 or EA-equivalent to quadratic 3-to-1 functions. Using the developed framework, we give the first proof that the infinite APN families of Budaghyan, Helleseth and Kaleyski; of Gologlu; and of Zheng, Kan, Li, Peng, and Tang have a Gold-like Walsh spectrum. We also give a simpler univariate representation of the Gogloglu family for dimensions n = 2m with m odd than the ones currently available in the literature. We conduct a computational search for quadratic 3-to-1 functions in even dimensions n ≤ 12. We find one new APN instance for n = 8, six new APN instances for n = 10, and the first sporadic APN instance for n = 12 since 2006. We provide a list of all known 3-to-1 APN functions for n ≤ 12.