Search Results - "Lafitte, Frederic"

Information-Theoretic Inference of Large Transcriptional Regulatory Networks by Meyer, Patrick, Kontos, Kevin, Lafitte, Frederic, Bontempi, Gianluca

“…The paper presents MRNET, an original method for inferring genetic networks from microarray data. The method is based on maximum relevance/minimum redundancy…”
Get full text

minet: A R/Bioconductor package for inferring large transcriptional networks using mutual information by Meyer, Patrick E, Lafitte, Frédéric, Bontempi, Gianluca

“…This paper presents the R/Bioconductor package minet (version 1.1.6) which provides a set of functions to infer mutual information networks from a dataset…”
Get full text

A weakness in OCB3 used with short nonces allowing for a break of authenticity and confidentiality by Liénardy, Jean, Lafitte, Frédéric

“…OCB3 is a mature and provably secure authenticated encryption mode of operation which allows for associated data (AEAD). This note reports a small flaw in the…”
Get full text

Blinded additively homomorphic encryption schemes for self-tallying voting by Dossogne, Jérôme, Lafitte, Frédéric

“…In this paper, we propose a self-tallying election protocol based public key homomorphic encryption. The additive homomorphism allows a set of participants…”
Get full text

SAT based analysis of LTE stream cipher ZUC by Lafitte, Frédéric, Markowitch, Olivier, Van Heule, Dirk

“…Mobile security is of paramount importance. The security of LTE (long term evolution of radio networks), which is currently widely deployed as a long-term…”
Get full text

Safe cryptographic random number generation using untrusted generators by Bruyninckx, Helena, Lafitte, Frédaíc, Van Heule, Dirk

“…The security of many cryptographic applications relies heavily on the quality of the random numbers used. Therefore, random number generation is one of the…”
Get full text

Information-theoretic inference of large transcriptional regulatory networks by Meyer, Patrick E, Kontos, Kevin, Lafitte, Frederic, Bontempi, Gianluca

“…The paper presents MRNET, an original method for inferring genetic networks from microarray data. The method is based on maximum relevance/minimum redundancy…”
Get full text