Generalized Power Attacks against Crypto Hardware using Long-Range Deep Learning

arXiv:2306.07249v2 Announce Type: replace
Abstract: To make cryptographic processors more resilient against side-channel attacks, engineers have developed various countermeasures. However, the effectiveness of these countermeasures is often uncertain, as it depends on the complex interplay between software and hardware. Assessing a countermeasure's effectiveness using profiling techniques or machine learning so far requires significant expertise and effort to be adapted to new targets which makes those assessments expensive. We argue that including cost-effective automated attacks will help chip design teams to …

arxiv attacks channel countermeasures crypto cryptographic cs.cr deep learning engineers hardware machine machine learning power processors profiling resilient side-channel side-channel attacks software techniques