Eavesdropping Attack Detection Using Machine Learning in Network-on-Chip Architectures

Abstract:

This article develops a machine-learning-based detection framework to detect eavesdropping attacks on networks-on-chip (NoCs).

This article develops a machine-learning-based detection framework to detect eavesdropping attacks on networks-on-chip (NoCs).

Published in: IEEE Design & Test ( Volume: 39, Issue: 6, December 2022)

Page(s): 28 - 38

Date of Publication: 30 August 2022

DOI: 10.1109/MDAT.2022.3202995

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