measuring the effectiveness of dpa attacks- from the perspective of distinguishers statistical characteristics

	measuring the effectiveness of dpa attacks- from the perspective of distinguishers statistical characteristics
	Huang Jingang; Zhou Yongbin; Liu Jiye
	2010
会议名称	2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
会议录名称	Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
页码	161-168
会议日期	44021
会议地点	Chengdu, China
出版地	United States
ISBN	9781420000000
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, Chinese Academy of Sciences, 19A Yuquan Lu, Beijing, lO0049, China
摘要	Distinguisher serves as an essential component in DPA attacks and should to some extent influence behaviors of these attacks. Motivated by this, we proposed a sound approach to evaluating the effectiveness of DPA attacks from the perspective of distinguishers statistical characteristics. For this propose, we formally defined the notion of Gaussian Distinguisher in one typical DP A attack setting and then proved that two most widely used DPA distinguishers (namely difference-of-means test and Pearson correlation coefficient) were Gaussian. After that, Distinctive Level, a useful quantitative metric, was introduced to evaluate the effectiveness of DPA attacks. This metric virtually equips the designer with the capability of judging to what extent DPA attacks will succeed. We performed experiments using both simulated and real power traces afterwards, the results of which evidently demonstrated the validity and the effectiveness of the methods we had proposed. © 2010 IEEE.
关键词	Computer Science Correlation Methods Information Technology Signal Analysis
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/8824
专题	基础软件国家工程研究中心
推荐引用方式 GB/T 7714	Huang Jingang,Zhou Yongbin,Liu Jiye. measuring the effectiveness of dpa attacks- from the perspective of distinguishers statistical characteristics[C]. United States,2010:161-168.

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