53 résultats
-
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[…] -
Search-Based Local Black-Box Deobfuscation: Understand, Improve and Mitigate
Orateur : Grégoire Menguy (CEA LIST)
Code obfuscation aims at protecting Intellectual Property and other secrets embedded into software from being retrieved. Recent works leverage advances in artificial intelligence (AI) with the hope of getting blackbox deobfuscators completely immune to standard (whitebox) protection mechanisms. While promising, this new field of AI-based, and more specifically search-based blackbox deobfuscation,[…] -
Model Stealing Attacks Against Inductive Graph Neural Networks
Orateur : Yufei Han (INRIA)
Many real-world data come in the form of graphs. Graph neural networks (GNNs), a new family of machine learning (ML) models, have been proposed to fully leverage graph data to build powerful applications. In particular, the inductive GNNs, which can generalize to unseen data, become mainstream in this direction. Machine learning models have shown great potential in various tasks and have been[…]