4 papers · 1 filter
Playing with blocks: Toward re-usable deep learning models for side-channel profiled attacks
Servio Paguada, Lejla Batina, Ileana Buhan +1
This paper introduces a deep learning modular network for side-channel analysis. Our deep learning approach features the capability to exchange part of it (modules) with others net…
Sniper Backdoor: Single Client Targeted Backdoor Attack in Federated Learning
Gorka Abad, Servio Paguada, Oguzhan Ersoy +3
Federated Learning (FL) enables collaborative training of Deep Learning (DL) models where the data is retained locally. Like DL, FL has severe security weaknesses that the attacker…
Being Patient and Persistent: Optimizing An Early Stopping Strategy for Deep Learning in Profiled Attacks
Servio Paguada, Lejla Batina, Ileana Buhan +1
The absence of an algorithm that effectively monitors deep learning models used in side-channel attacks increases the difficulty of evaluation. If the attack is unsuccessful, the q…
The uncertainty of Side-Channel Analysis: A way to leverage from heuristics
Unai Rioja, Servio Paguada, Lejla Batina +1
Performing a comprehensive side-channel analysis evaluation of small embedded devices is a process known for its variability and complexity. In real-world experimental setups, the…