Paper 2023/1722 Original: eprint.iacr.org/2023/1722 ↗

Quantitative Fault Injection Analysis

Abstract

Active fault injection is a credible threat to real-world digital systems computing on sensitive data. Arguing about security in the presence of faults is non-trivial, and state-of-the-art criteria are overly conservative and lack the ability of fine-grained comparison. However, comparing two alternative implementations for their security is required to find a satisfying compromise between security and performance. In addition, the comparison of alternative fault scenarios can help optimize the implementation of effective countermeasures. In this work, we use quantitative information flow analysis to establish a vulnerability metric for hardware circuits under fault injection that measures the severity of an attack in terms of information leakage. Potential use cases range from comparing implementations with respect to their vulnerability to specific fault scenarios to optimizing countermeasures. We automate the computation of our metric by integrating it into a state-of-the-art evaluation tool for physical attacks and provide new insights into the security under an active fault attacker.