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	Quantification of side-channel information leaks based on data complexity measures for web browsing (EI收录)
	He, Zhi-Min[1]; Chan, Patrick P. K.[1]; Yeung, Daniel S.[1]; Pedrycz, Witold[2,3]; Ng, Wing W. Y.[1]
刊名	International Journal of Machine Learning and Cybernetics
	2015
卷号	6页码:607-619
关键词	Codes (symbols) Complex networks Social networking (online) Web browsers Websites
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2211155
专题	华南理工大学
作者单位	1.[1] School of Computer Science and Engineering, South China University of Technology, Guangzhou, China 2.[2] Department of Electrical and Computer Engineering, University of Alberta, Edmonton 3.AB, Canada 4.[3] Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
推荐引用方式 GB/T 7714	He, Zhi-Min[1],Chan, Patrick P. K.[1],Yeung, Daniel S.[1],等. Quantification of side-channel information leaks based on data complexity measures for web browsing (EI收录)[J]. International Journal of Machine Learning and Cybernetics,2015,6:607-619.
APA	He, Zhi-Min[1],Chan, Patrick P. K.[1],Yeung, Daniel S.[1],Pedrycz, Witold[2,3],&Ng, Wing W. Y.[1].(2015).Quantification of side-channel information leaks based on data complexity measures for web browsing (EI收录).International Journal of Machine Learning and Cybernetics,6,607-619.
MLA	He, Zhi-Min[1],et al."Quantification of side-channel information leaks based on data complexity measures for web browsing (EI收录)".International Journal of Machine Learning and Cybernetics 6(2015):607-619.

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