an efficient leakage characterization method for profiled power analysis attacks

ISCAS OpenIR

	an efficient leakage characterization method for profiled power analysis attacks
	Zhang Hailong; Zhou Yongbin; Feng Dengguo
	2012
会议名称	14th International Conference on Information Security and Cryptology, ICISC 2011
会议录名称	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
页码	61-73
会议日期	November 30, 2011 - December 2, 2011
会议地点	Seoul, Korea, Republic of
收录类别	EI
ISSN	0302-9743
ISBN	9783642319112
部门归属	(1) State Key Laboratory of Information Security Institute of Software Chinese Academy of Sciences P.O. Box 8718 Beijing 100190 China; (2) Graduate University of Chinese Academy of Sciences 19A Yuquan Lu Beijing 100049 China
摘要	In typical Profiled Power Analysis Attacks, like Template Attack (TA) and Stochastic Model based Power Analysis (SMPA), key-recovery efficiency is strongly influenced by the accuracy of characterization in profiling. In order to accurately characterize signals and noises in different times, a large number of power traces is usually needed in profiling. However, a large number of power traces is not always available. In this case, the accuracy of characterization is rapidly degraded, and so it is with the efficiency of subsequent key-recovery. In light of this, we present an efficient Covariance Analysis based Characterization Method (CACM for short) to deal with the problem of more accurate leakage characterization with less power traces. We perform experimental power analysis attacks against an AES software implementation on STC89C52 microcontroller, then conduct a comparative study of the effectiveness of these profiled attacks. The results firmly support the validity and efficiency of our method. © 2012 Springer-Verlag.; In typical Profiled Power Analysis Attacks, like Template Attack (TA) and Stochastic Model based Power Analysis (SMPA), key-recovery efficiency is strongly influenced by the accuracy of characterization in profiling. In order to accurately characterize signals and noises in different times, a large number of power traces is usually needed in profiling. However, a large number of power traces is not always available. In this case, the accuracy of characterization is rapidly degraded, and so it is with the efficiency of subsequent key-recovery. In light of this, we present an efficient Covariance Analysis based Characterization Method (CACM for short) to deal with the problem of more accurate leakage characterization with less power traces. We perform experimental power analysis attacks against an AES software implementation on STC89C52 microcontroller, then conduct a comparative study of the effectiveness of these profiled attacks. The results firmly support the validity and efficiency of our method. © 2012 Springer-Verlag.
关键词	Characterization Efficiency Security Of Data
主办者	National Security Research Institute (NSRI); Electronics and Telecommunications Research Institute (ETRI); Korea Internet and Security Agency (KISA); Ministry of Public Administration and Security (MOPAS)
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15760
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Zhang Hailong,Zhou Yongbin,Feng Dengguo. an efficient leakage characterization method for profiled power analysis attacks[C],2012:61-73.