Enabling Side‐Channel Attacks on Post‐Quantum Protocols through Machine Learning

The primary purpose of this project is to enable single-trace power side-channel attacks on post-quantum key-exchange protocols using machine learning and to quantify the strength of timing obfuscation defenses against those attacks. The central question to be addressed is whether machine-learning classifiers provide stronger attacks compared to the conventional ones in the context of post-quantum cryptosystems, and to what extent can obfuscation methods hide the vulnerability.

Project PI: Aydin Aysu

Research Thrust: Reliability and Security

Research Timeline Jan 1, 2019 – Dec 31, 2020