Publications associées (32)

Machine Learning Security Against Data Poisoning: Are We There Yet?

Kathrin Grosse

Poisoning attacks compromise the training data utilized to train machine learning (ML) models, diminishing their overall performance, manipulating predictions on specific test samples, and implanting backdoors. This article thoughtfully explores these atta ...
Ieee Computer Soc2024

Towards more Practical Threat Models in Artificial Intelligence Security

Alexandre Massoud Alahi, Kathrin Grosse

Recent works have identified a gap between research and practice in artificial intelligence security: threats studied in academia do not always reflect the practical use and security risks of AI. For example, while models are often studied in isolation, th ...
arXiv2023

The Role of Hub Neurons in Modulating Cortical Dynamics

Henry Markram, Oren Amsalem, Idan Segev, Eyal Gal, Michael London

Many neurodegenerative diseases are associated with the death of specific neuron types in particular brain regions. What makes the death of specific neuron types particularly harmful for the integrity and dynamics of the respective network is not well unde ...
2021

Time-Synchronization Attacks against Critical Infrastructures and their Mitigation

Marguerite Marie Nathalie Delcourt

This work focuses on the security of critical infrastructures against time-synchronization attacks (TSA). A TSA can impact any network that relies on the dynamic analysis of data, by altering the time synchronization between its nodes. Such attacked networ ...
EPFL2021

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