Research Article
POSTER: Using Improved Singular Value Decomposition to Enhance Correlation Power Analysis
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@INPROCEEDINGS{10.1007/978-3-319-28865-9_39, author={Degang Sun and Xinping Zhou and Zhu Wang and Changhai Ou and Weiqing Huang and Juan Ai}, title={POSTER: Using Improved Singular Value Decomposition to Enhance Correlation Power Analysis}, proceedings={Security and Privacy in Communication Networks. 11th International Conference, SecureComm 2015, Dallas, TX, USA, October 26-29, 2015, Revised Selected Papers}, proceedings_a={SECURECOMM}, year={2016}, month={2}, keywords={Improved Singular Value Decomposition Side Channel Attack Correlation Power Analysis Selecting traces}, doi={10.1007/978-3-319-28865-9_39} }- Degang Sun
Xinping Zhou
Zhu Wang
Changhai Ou
Weiqing Huang
Juan Ai
Year: 2016
POSTER: Using Improved Singular Value Decomposition to Enhance Correlation Power Analysis
SECURECOMM
Springer
DOI: 10.1007/978-3-319-28865-9_39
Abstract
Correlation Power Analysis (CPA) is one of effective means of power analysis in side channel analysis. The noisy power traces can affect the power of CPA. It is significant to select the helpful power traces to improve the efficiency of analysis. In this paper, we present a new pre-processing method that is based on Improved Singular Value Decomposition (ISVD) for selecting the traces when using CPA to attack. The ISVD is a combination of SVD and Z-score. Experimental results show that our method is effective to improve the efficiency when analyzing both the unprotected implementation and the masked implementation.
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