M
Matthieu Finiasz
Researcher at French Institute for Research in Computer Science and Automation
Publications - 35
Citations - 1408
Matthieu Finiasz is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Cryptosystem & Cryptography. The author has an hindex of 19, co-authored 35 publications receiving 1267 citations. Previous affiliations of Matthieu Finiasz include École Polytechnique Fédérale de Lausanne & École Normale Supérieure.
Papers
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Book ChapterDOI
How to Achieve a McEliece-Based Digital Signature Scheme
TL;DR: This paper disproves the belief that code-based cryptosystems like McEliece do not allow practical digital signatures, and shows a way to build a practical signature scheme based on coding theory.
Book ChapterDOI
Security Bounds for the Design of Code-Based Cryptosystems
TL;DR: Lower bounds are given on the work factor of idealized versions of code-based cryptography algorithms, taking into account all possible tweaks which could improve their practical complexity.
Book ChapterDOI
A family of fast syndrome based cryptographic hash functions
TL;DR: This article presents a family of secure hash functions, whose security is directly related to the syndrome decoding problem from the theory of error-correcting codes, and proposes a few sets of parameters giving a good security and either a faster hashing or a shorter description for the function.
Proceedings ArticleDOI
Recovering a code's length and synchronization from a noisy intercepted bitstream
Mathieu Cluzeau,Matthieu Finiasz +1 more
TL;DR: Two algorithms are presented, one due to Valembois and the other brand new, useful in different contexts, able to verify if a given length/synchronization is correct and practically recover the synchronization of several codes.
Proceedings ArticleDOI
Reconstruction of punctured convolutional codes
Mathieu Cluzeau,Matthieu Finiasz +1 more
TL;DR: Compared to existing techniques, this new technique to reconstruct punctured convolutional codes from a noisy intercepted bit-stream has two major advantages: it can tolerate much higher noise levels in the bitstream and it is able to recover the best possible decoder.