Too Many Cores to Care: When Parallelism Breaks Side-Channel Attacks
Cores are usually discussed as a performance story. More cores, more parallelism, less latency, happier product manager. Security people, being paid to ruin everyone’s afternoon, usually hear something else: more switching activity, more leakage, more things an attacker can measure. This paper complicates that instinct in a useful way. In Influence of Parallelism in Vector-Multiplication Units on Correlation Power Analysis, Manuel Brosch, Matthias Probst, Stefan Kögler, and Georg Sigl study a very specific question: when a neural-network accelerator processes the same input value across multiple processing elements, each with a different secret weight, what happens to correlation power analysis?1 ...