| Title | Attacking Masked Cryptographic Implementations: Information-Theoretic Bounds |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Cheng, Wei, Liu, Yi, Guilley, Sylvain, Rioul, Olivier |
| Conference Name | 2022 IEEE International Symposium on Information Theory (ISIT) |
| Date Published | jun |
| Keywords | Analytical models, Collaboration, composability, compositionality, Human Behavior, human factors, information theoretic security, Information-Theoretic Metric, Masking Scheme, maximum likelihood estimation, Measurement, Metrics, Monte Carlo methods, Monte-Carlo simulation, Numerical models, policy-based governance, pubcrawl, resilience, Resiliency, Scalability, side-channel analysis, side-channel attacks, Success Rate, Upper bound |
| Abstract | Measuring the information leakage is critical for evaluating the practical security of cryptographic devices against side-channel analysis. Information-theoretic measures can be used (along with Fano's inequality) to derive upper bounds on the success rate of any possible attack in terms of the number of side-channel measurements. Equivalently, this gives lower bounds on the number of queries for a given success probability of attack. In this paper, we consider cryptographic implementations protected by (first-order) masking schemes, and derive several information-theoretic bounds on the efficiency of any (second-order) attack. The obtained bounds are generic in that they do not depend on a specific attack but only on the leakage and masking models, through the mutual information between side-channel measurements and the secret key. Numerical evaluations confirm that our bounds reflect the practical performance of optimal maximum likelihood attacks. |
| DOI | 10.1109/ISIT50566.2022.9834556 |
| Citation Key | cheng_attacking_2022 |
Attacking Masked Cryptographic Implementations: Information-Theoretic Bounds