Artificial Intelligence (AI) has sparked an unexpected, fast-paced evolution in the services and manufacturing industries.
At the same time, the uncontrolled use of such technology has greatly expanded the existing attack surface, bringing new security, safety, and privacy issues.
Among the possible attack vectors, side-channel attacks are an emerging threat.
Through side-channel analysis techniques, a malicious user may exfiltrate information on the AI's IP, gaining a significant economic advantage over competitors or paving the way to more dangerous attacks.

In this context, the attack-related literature advances quickly: Red team can already exploit side channels to recover the full architecture of a TPU-hosted AI model, and combine side-channel information with analytical techniques to recover the whole set of parameters of an AI model.

But where is Blue Team?

With this talk, I provide a comprehensive overview of the existing methodologies to protect AI against side-channel attacks. Starting with classic countermeasures borrowed from the cryptology field, and exploring new countermeasures underpinned by AI characteristics, I show how Blue Team is defying Red Team efforts, and how it is supporting the design of trustworthy AI.