CRYPTO '99 Proceedings of the 19th Annual International Cryptology Conference on Advances in Cryptology
Differential Power Analysis in the Presence of Hardware Countermeasures
CHES '00 Proceedings of the Second International Workshop on Cryptographic Hardware and Embedded Systems
Power analysis attacks and countermeasures for cryptographic algorithms
Power analysis attacks and countermeasures for cryptographic algorithms
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
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
Improving differential power analysis by elastic alignment
CT-RSA'11 Proceedings of the 11th international conference on Topics in cryptology: CT-RSA 2011
First principal components analysis: a new side channel distinguisher
ICISC'10 Proceedings of the 13th international conference on Information security and cryptology
Template attacks in principal subspaces
CHES'06 Proceedings of the 8th international conference on Cryptographic Hardware and Embedded Systems
CARDIS'11 Proceedings of the 10th IFIP WG 8.8/11.2 international conference on Smart Card Research and Advanced Applications
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Improving side-channel analysis with optimal linear transforms
CARDIS'12 Proceedings of the 11th international conference on Smart Card Research and Advanced Applications
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Differential Power Analysis (DPA) is commonly used to obtain information about the secret key used in cryptographic devices. Countermeasures against DPA can cause power traces to be misaligned, which reduces the effectiveness of DPA. Principal Component Analysis (PCA) is a powerful tool, which is used in different research areas to identify trends in a data set. Principal Components are introduced to describe the relationships within the data. The largest principal components capture the data with the largest variance. These Principal Components can be used to reduce the noise in a data set or to transform the data set in terms of these components. We propose the use of Principal Component Analysis to improve the correlation for the correct key guess for DPA attacks on software DES traces and show that it can also be applied for other algorithms. We also introduce a new way of determining key candidates by calculating the absolute average value of the correlation traces after a DPA attack on a PCA-transformed trace. We conclude that Principal Component Analysis can successfully be used as a preprocessing technique to reduce the noise in a trace set and improve the correlation for the correct key guess using Differential Power Analysis attacks.