@inproceedings{8339,
abstract = {Discrete Gaussian distributions over lattices are central to lattice-based cryptography, and to the computational and mathematical aspects of lattices more broadly. The literature contains a wealth of useful theorems about the behavior of discrete Gaussians under convolutions and related operations. Yet despite their structural similarities, most of these theorems are formally incomparable, and their proofs tend to be monolithic and written nearly “from scratch,” making them unnecessarily hard to verify, understand, and extend.
In this work we present a modular framework for analyzing linear operations on discrete Gaussian distributions. The framework abstracts away the particulars of Gaussians, and usually reduces proofs to the choice of appropriate linear transformations and elementary linear algebra. To showcase the approach, we establish several general properties of discrete Gaussians, and show how to obtain all prior convolution theorems (along with some new ones) as straightforward corollaries. As another application, we describe a self-reduction for Learning With Errors (LWE) that uses a fixed number of samples to generate an unlimited number of additional ones (having somewhat larger error). The distinguishing features of our reduction are its simple analysis in our framework, and its exclusive use of discrete Gaussians without any loss in parameters relative to a prior mixed discrete-and-continuous approach.
As a contribution of independent interest, for subgaussian random matrices we prove a singular value concentration bound with explicitly stated constants, and we give tighter heuristics for specific distributions that are commonly used for generating lattice trapdoors. These bounds yield improvements in the concrete bit-security estimates for trapdoor lattice cryptosystems.},
author = {Genise, Nicholas and Micciancio, Daniele and Peikert, Chris and Walter, Michael},
booktitle = {23rd IACR International Conference on the Practice and Theory of Public-Key Cryptography},
isbn = {9783030453732},
issn = {16113349},
location = {Edinburgh, United Kingdom},
pages = {623--651},
publisher = {Springer Nature},
title = {{Improved discrete Gaussian and subgaussian analysis for lattice cryptography}},
doi = {10.1007/978-3-030-45374-9_21},
volume = {12110},
year = {2020},
}
@inproceedings{7411,
abstract = {Proofs of sequential work (PoSW) are proof systems where a prover, upon receiving a statement χ and a time parameter T computes a proof ϕ(χ,T) which is efficiently and publicly verifiable. The proof can be computed in T sequential steps, but not much less, even by a malicious party having large parallelism. A PoSW thus serves as a proof that T units of time have passed since χ
was received.
PoSW were introduced by Mahmoody, Moran and Vadhan [MMV11], a simple and practical construction was only recently proposed by Cohen and Pietrzak [CP18].
In this work we construct a new simple PoSW in the random permutation model which is almost as simple and efficient as [CP18] but conceptually very different. Whereas the structure underlying [CP18] is a hash tree, our construction is based on skip lists and has the interesting property that computing the PoSW is a reversible computation.
The fact that the construction is reversible can potentially be used for new applications like constructing proofs of replication. We also show how to “embed” the sloth function of Lenstra and Weselowski [LW17] into our PoSW to get a PoSW where one additionally can verify correctness of the output much more efficiently than recomputing it (though recent constructions of “verifiable delay functions” subsume most of the applications this construction was aiming at).},
author = {Abusalah, Hamza M and Kamath Hosdurg, Chethan and Klein, Karen and Pietrzak, Krzysztof Z and Walter, Michael},
booktitle = {Advances in Cryptology – EUROCRYPT 2019},
isbn = {9783030176556},
issn = {0302-9743},
location = {Darmstadt, Germany},
pages = {277--291},
publisher = {Springer International Publishing},
title = {{Reversible proofs of sequential work}},
doi = {10.1007/978-3-030-17656-3_10},
volume = {11477},
year = {2019},
}
@inbook{6726,
abstract = {Randomness is an essential part of any secure cryptosystem, but many constructions rely on distributions that are not uniform. This is particularly true for lattice based cryptosystems, which more often than not make use of discrete Gaussian distributions over the integers. For practical purposes it is crucial to evaluate the impact that approximation errors have on the security of a scheme to provide the best possible trade-off between security and performance. Recent years have seen surprising results allowing to use relatively low precision while maintaining high levels of security. A key insight in these results is that sampling a distribution with low relative error can provide very strong security guarantees. Since floating point numbers provide guarantees on the relative approximation error, they seem a suitable tool in this setting, but it is not obvious which sampling algorithms can actually profit from them. While previous works have shown that inversion sampling can be adapted to provide a low relative error (Pöppelmann et al., CHES 2014; Prest, ASIACRYPT 2017), other works have called into question if this is possible for other sampling techniques (Zheng et al., Eprint report 2018/309). In this work, we consider all sampling algorithms that are popular in the cryptographic setting and analyze the relationship of floating point precision and the resulting relative error. We show that all of the algorithms either natively achieve a low relative error or can be adapted to do so.},
author = {Walter, Michael},
booktitle = {Progress in Cryptology – AFRICACRYPT 2019},
editor = {Buchmann, J and Nitaj, A and Rachidi, T},
isbn = {9783030236953},
issn = {0302-9743},
location = {Rabat, Morocco},
pages = {157--180},
publisher = {Springer Nature},
title = {{Sampling the integers with low relative error}},
doi = {10.1007/978-3-030-23696-0_9},
volume = {11627},
year = {2019},
}
@inproceedings{300,
abstract = {We introduce a formal quantitative notion of “bit security” for a general type of cryptographic games (capturing both decision and search problems), aimed at capturing the intuition that a cryptographic primitive with k-bit security is as hard to break as an ideal cryptographic function requiring a brute force attack on a k-bit key space. Our new definition matches the notion of bit security commonly used by cryptographers and cryptanalysts when studying search (e.g., key recovery) problems, where the use of the traditional definition is well established. However, it produces a quantitatively different metric in the case of decision (indistinguishability) problems, where the use of (a straightforward generalization of) the traditional definition is more problematic and leads to a number of paradoxical situations or mismatches between theoretical/provable security and practical/common sense intuition. Key to our new definition is to consider adversaries that may explicitly declare failure of the attack. We support and justify the new definition by proving a number of technical results, including tight reductions between several standard cryptographic problems, a new hybrid theorem that preserves bit security, and an application to the security analysis of indistinguishability primitives making use of (approximate) floating point numbers. This is the first result showing that (standard precision) 53-bit floating point numbers can be used to achieve 100-bit security in the context of cryptographic primitives with general indistinguishability-based security definitions. Previous results of this type applied only to search problems, or special types of decision problems.},
author = {Micciancio, Daniele and Walter, Michael},
location = {Tel Aviv, Israel},
pages = {3 -- 28},
publisher = {Springer},
title = {{On the bit security of cryptographic primitives}},
doi = {10.1007/978-3-319-78381-9_1},
volume = {10820},
year = {2018},
}