International Association for Cryptologic Research

International Association
for Cryptologic Research


Pierrick Méaux


Learning Parity with Physical Noise: Imperfections, Reductions and FPGA Prototype 📺
Hard learning problems are important building blocks for the design of various cryptographic functionalities such as authentication protocols and post-quantum public key encryption. The standard implementations of such schemes add some controlled errors to simple (e.g., inner product) computations involving a public challenge and a secret key. Hard physical learning problems formalize the potential gains that could be obtained by leveraging inexact computing to directly generate erroneous samples. While they have good potential for improving the performances and physical security of more conventional samplers when implemented in specialized integrated circuits, it remains unknown whether physical defaults that inevitably occur in their instantiation can lead to security losses, nor whether their implementation can be viable on standard platforms such as FPGAs. We contribute to these questions in the context of the Learning Parity with Physical Noise (LPPN) problem by: (1) exhibiting new (output) data dependencies of the error probabilities that LPPN samples may suffer from; (2) formally showing that LPPN instances with such dependencies are as hard as the standard LPN problem; (3) analyzing an FPGA prototype of LPPN processor that satisfies basic security and performance requirements.
Efficient and Private Computations with Code-Based Masking 📺
Code-based masking is a very general type of masking scheme that covers Boolean masking, inner product masking, direct sum masking, and so on. The merits of the generalization are twofold. Firstly, the higher algebraic complexity of the sharing function decreases the information leakage in “low noise conditions” and may increase the “statistical security order” of an implementation (with linear leakages). Secondly, the underlying error-correction codes can offer improved fault resistance for the encoded variables. Nevertheless, this higher algebraic complexity also implies additional challenges. On the one hand, a generic multiplication algorithm applicable to any linear code is still unknown. On the other hand, masking schemes with higher algebraic complexity usually come with implementation overheads, as for example witnessed by inner-product masking. In this paper, we contribute to these challenges in two directions. Firstly, we propose a generic algorithm that allows us (to the best of our knowledge for the first time) to compute on data shared with linear codes. Secondly, we introduce a new amortization technique that can significantly mitigate the implementation overheads of code-based masking, and illustrate this claim with a case study. Precisely, we show that, although performing every single code-based masked operation is relatively complex, processing multiple secrets in parallel leads to much better performances. This property enables code-based masked implementations of the AES to compete with the state-of-the-art in randomness complexity. Since our masked operations can be instantiated with various linear codes, we hope that these investigations open new avenues for the study of code-based masking schemes, by specializing the codes for improved performances, better side-channel security or improved fault tolerance.
Exploring Crypto-Physical Dark Matter and Learning with Physical Rounding: Towards Secure and Efficient Fresh Re-Keying 📺
State-of-the-art re-keying schemes can be viewed as a tradeoff between efficient but heuristic solutions based on binary field multiplications, that are only secure if implemented with a sufficient amount of noise, and formal but more expensive solutions based on weak pseudorandom functions, that remain secure if the adversary accesses their output in full. Recent results on “crypto dark matter” (TCC 2018) suggest that low-complexity pseudorandom functions can be obtained by mixing linear functions over different small moduli. In this paper, we conjecture that by mixing some matrix multiplications in a prime field with a physical mapping similar to the leakage functions exploited in side-channel analysis, we can build efficient re-keying schemes based on “crypto-physical dark matter”, that remain secure against an adversary who can access noise-free measurements. We provide first analyzes of the security and implementation properties that such schemes provide. Precisely, we first show that they are more secure than the initial (heuristic) proposal by Medwed et al. (AFRICACRYPT 2010). For example, they can resist attacks put forward by Belaid et al. (ASIACRYPT 2014), satisfy some relevant cryptographic properties and can be connected to a “Learning with Physical Rounding” problem that shares some similarities with standard learning problems. We next show that they are significantly more efficient than the weak pseudorandom function proposed by Dziembowski et al. (CRYPTO 2016), by exhibiting hardware implementation results.
On the Concrete Security of Goldreich’s Pseudorandom Generator
Local pseudorandom generators allow to expand a short random string into a long pseudo-random string, such that each output bit depends on a constant number d of input bits. Due to its extreme efficiency features, this intriguing primitive enjoys a wide variety of applications in cryptography and complexity. In the polynomial regime, where the seed is of size n and the output of size $$n^{\textsf {s}}$$ for $$\textsf {s}> 1$$ , the only known solution, commonly known as Goldreich’s PRG, proceeds by applying a simple d-ary predicate to public random size-d subsets of the bits of the seed.While the security of Goldreich’s PRG has been thoroughly investigated, with a variety of results deriving provable security guarantees against class of attacks in some parameter regimes and necessary criteria to be satisfied by the underlying predicate, little is known about its concrete security and efficiency. Motivated by its numerous theoretical applications and the hope of getting practical instantiations for some of them, we initiate a study of the concrete security of Goldreich’s PRG, and evaluate its resistance to cryptanalytic attacks. Along the way, we develop a new guess-and-determine-style attack, and identify new criteria which refine existing criteria and capture the security guarantees of candidate local PRGs in a more fine-grained way.
Boolean functions with restricted input and their robustness; application to the FLIP cipher
Claude Carlet Pierrick Méaux Yann Rotella
We study the main cryptographic features of Boolean functions (balancedness, nonlinearity, algebraic immunity) when, for a given number n of variables, the input to these functions is restricted to some subset E of