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PRODID:-//GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen - ECPv5.7.0//NONSGML v1.0//EN
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METHOD:PUBLISH
X-WR-CALNAME:GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
X-ORIGINAL-URL:https://www.greyc.fr
X-WR-CALDESC:évènements pour GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20230326T010000
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TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20231029T010000
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20231107T100000
DTEND;TZID=Europe/Paris:20231107T110000
DTSTAMP:20260314T101041
CREATED:20230911T083351Z
LAST-MODIFIED:20231013T150334Z
UID:11246-1699351200-1699354800@www.greyc.fr
SUMMARY:Séminaire Algorithmique : « FHE & AI: a Concrete Use-Case »\, Bastien Vialla (Orange Labs\, Caen)
DESCRIPTION:In the Franco-German collaborative project CRYPTECS\, Orange Innovation explores privacy-preserving technologies for industrial applications. A prime use-case is detecting compromised computers through network traffic analysis. We have developed efficient AI models tailored for this. Our aim is to deploy these models while safeguarding both the model and network data\, making Fully Homomorphic Encryption (FHE) an ideal theoretical solution. \nThis presentation is at the cross-section of cybersecurity\, AI and cryptography. We will delve into the broader context of the use-case\, the AI models used\, the adaptations required in training to accommodate FHE\, the consequential impact on prediction quality\, and overall performance metrics.
URL:https://www.greyc.fr/event/seminaire-algorithmique-bastien-vialla-orange-labs-caen/
LOCATION:Sciences 3- S3 351
CATEGORIES:General,News,Séminaire Algo
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