61 résultats
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Learning-Based Network Intrusion Detection: an Imbalanced, Constantly Evolving and Timely Problem
Orateur : Maxime Pelcat (INSA Rennes)
Network intrusion detection systems (NIDS) observe network traffic and aim to pinpoint intrusions, i.e. effective threats on the integrity, availability or confidentiality of services and data provided by this network. There are two types of NIDS:1) signature-based intrusion detection systems that identify known intrusions by referring to an existing knowledge base, and2) anomaly-based intrusion[…] -
L’empoisonnement de données semble-t-il un risque réaliste ?
Orateur : Adrien Chan-Hon-Tong (ONERA)
Les attaques adversaires ont rencontré un fort écho dans la communauté de vision par ordinateur. Pour autant, via ce type d’attaque, un hacker ne peut modifier le comportement de l’algorithme ciblé que localement. Inversement, l’empoisonnement de données est en mesure de modifier globalement le comportement de l’algorithme visé, et, il n’est pas forcément détectable par un opérateur notamment si[…] -
A Fundamental Approach to Cyber Risk Analysis
Orateur : Rainer Böhme (Universität Innsbruck)
This paper provides a framework actuaries can use to think about cyber risk. We propose a differentiated view of cyber versus conventional risk by separating the nature of risk arrival from the target exposed to risk. Our review synthesizes the liter- ature on cyber risk analysis from various disciplines, including computer and network engineering, economics, and actuarial sciences. As a result,[…] -
Port Contention Goes Portable: Port Contention Side Channels in Web Browsers
Orateur : Thomas Rokicki (Univ Rennes, CNRS, IRISA)
Microarchitectural side-channel attacks can derive secrets from the execution of vulnerable programs. Their implementation in web browsers represents a considerable extension of their attack surface, as a user simply browsing a malicious website, or even a malicious third-party advertisement in a benign cross-origin isolated website, can be a victim.In this talk, we present the first CPU port[…] -
On MILP modelisations
Orateur : Christina Boura (UVSQ, CNRS, LMV)
Modelizing a problem using linear constraints and solving it by some Mixed Integer Linear Programming (MILP) solver is a popular approach in many domains of computer science. In this talk we present and compare different new techniques to modelize any subset of {0,1}^n for MILP. We then discuss the efficiency of our models by applying them to the search of differential paths, a classical problem[…] -
Built on sand: on the security of Collaborative Machine Learning
Orateur : Dario Pasquini (EPFL)
This talk is about inaccurate assumptions, unrealistic trust models, and flawed methodologies affecting current collaborative machine learning techniques. In the presentation, we cover different security issues concerning both emerging approaches and well-established solutions in privacy-preserving collaborative machine learning. We start by discussing the inherent insecurity of Split Learning and[…]