The upward bias in measures of information derived from limited data samples
Neural Computation
CRYPTO '99 Proceedings of the 19th Annual International Cryptology Conference on Advances in Cryptology
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
Information Security and Cryptology --- ICISC 2008
A Unified Framework for the Analysis of Side-Channel Key Recovery Attacks
EUROCRYPT '09 Proceedings of the 28th Annual International Conference on Advances in Cryptology: the Theory and Applications of Cryptographic Techniques
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
FSE'05 Proceedings of the 12th international conference on Fast Software Encryption
A stochastic model for differential side channel cryptanalysis
CHES'05 Proceedings of the 7th international conference on Cryptographic hardware and embedded systems
Masked dual-rail pre-charge logic: DPA-resistance without routing constraints
CHES'05 Proceedings of the 7th international conference on Cryptographic hardware and embedded systems
Generic side-channel distinguishers: improvements and limitations
CRYPTO'11 Proceedings of the 31st annual conference on Advances in cryptology
An exploration of the kolmogorov-smirnov test as a competitor to mutual information analysis
CARDIS'11 Proceedings of the 10th IFIP WG 8.8/11.2 international conference on Smart Card Research and Advanced Applications
Selecting time samples for multivariate DPA attacks
CHES'12 Proceedings of the 14th 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
Applying remote side-channel analysis attacks on a security-enabled NFC tag
CT-RSA'13 Proceedings of the 13th international conference on Topics in Cryptology
Success through confidence: evaluating the effectiveness of a side-channel attack
CHES'13 Proceedings of the 15th international conference on Cryptographic Hardware and Embedded Systems
Profiling DPA: efficacy and efficiency trade-offs
CHES'13 Proceedings of the 15th international conference on Cryptographic Hardware and Embedded Systems
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The resistance of cryptographic implementations to sidechannel analysis is a matter of considerable interest to those concerned with information security. It is particularly desirable to identify the attack methodology (e.g. differential power analysis using correlation or distance-of-means as the distinguisher) able to produce the best results. Such attempts are complicated by the many and varied factors contributing to attack success: the device power consumption characteristics, an attacker's power model, the distinguisher by which measurements and model predictions are compared, the quality of the estimations, and so on. Previous work has delivered partial answers for certain restricted scenarios. In this paper we assess the effectiveness of mutual informationbased differential power analysis within a generic and comprehensive evaluation framework. Complementary to existing work, we present several notions/characterisations of attack success with direct implications for the amount of data required. We are thus able to identify scenarios in which mutual information offers performance advantages over other distinguishers. Furthermore we observe an interesting feature-unique to the mutual information based distinguisher-resembling a type of stochastic resonance, which could potentially enhance the effectiveness of such attacks over other methods in certain noisy scenarios.