Power Analysis, What Is Now Possible...
ASIACRYPT '00 Proceedings of the 6th International Conference on the Theory and Application of Cryptology and Information Security: Advances in Cryptology
CHES '02 Revised Papers from the 4th International Workshop on Cryptographic Hardware and Embedded Systems
Estimation of entropy and mutual information
Neural Computation
Power Analysis Attacks: Revealing the Secrets of Smart Cards (Advances in Information Security)
Power Analysis Attacks: Revealing the Secrets of Smart Cards (Advances in Information Security)
CHES '08 Proceeding sof the 10th international workshop on Cryptographic Hardware and Embedded Systems
Theoretical and Practical Aspects of Mutual Information Based Side Channel Analysis
ACNS '09 Proceedings of the 7th International Conference on Applied Cryptography and Network Security
Mutual Information Analysis: How, When and Why?
CHES '09 Proceedings of the 11th International Workshop on Cryptographic Hardware and Embedded Systems
Mutual Information Analysis: a Comprehensive Study
Journal of Cryptology - Special Issue on Hardware and Security
A formal study of power variability issues and side-channel attacks for nanoscale devices
EUROCRYPT'11 Proceedings of the 30th Annual international conference on Theory and applications of cryptographic techniques: advances in cryptology
A comprehensive evaluation of mutual information analysis using a fair evaluation framework
CRYPTO'11 Proceedings of the 31st annual conference on Advances in cryptology
FSE'05 Proceedings of the 12th international conference on Fast Software Encryption
Successfully attacking masked AES hardware implementations
CHES'05 Proceedings of the 7th international conference on Cryptographic hardware and embedded systems
Comparison between side-channel analysis distinguishers
ICICS'12 Proceedings of the 14th international conference on Information and Communications Security
SCA with magnitude squared coherence
CARDIS'12 Proceedings of the 11th international conference on Smart Card Research and Advanced Applications
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A theme of recent side-channel research has been the quest for distinguishers which remain effective even when few assumptions can be made about the underlying distribution of the measured leakage traces. The Kolmogorov-Smirnov (KS) test is a well known non-parametric method for distinguishing between distributions, and, as such, a perfect candidate and an interesting competitor to the (already much discussed) mutual information (MI) based attacks. However, the side-channel distinguisher based on the KS test statistic has received only cursory evaluation so far, which is the gap we narrow here. This contribution explores the effectiveness and efficiency of Kolmogorov-Smirnov analysis (KSA), and compares it with mutual information analysis (MIA) in a number of relevant scenarios ranging from optimistic first-order DPA to multivariate settings. We show that KSA shares certain ‘generic' capabilities in common with MIA whilst being more robust to noise than MIA in univariate settings. This has the practical implication that designers should consider results of KSA to determine the resilience of their designs against univariate power analysis attacks.