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	Hybrid Concentration Based Feature Extraction Approach for Malware Detection
	Zhang, Pengtao ; Tan, Ying
	2015
关键词	MALICIOUS EXECUTABLES VIRUS DETECTION SELECTION
英文摘要	In this paper, a hybrid concentration based feature extraction (HCFE) approach is proposed. The HCFE approach extracts the hybrid concentration (HC) of a sample in both the global resolution and the local resolution. The HC of a sample characterizes the sample more precisely and completely by taking the global information and local information into account at the same time. With the help of the co-operation of the global and local information, the HC discards the bias of the global concentration (GC) to the global information and the local concentration (LC) to the local information, respectively. In order to incorporate the HCFE approach into the procedure of malware detection, a HC-based malware detection (HCMD) method is proposed. Eight groups of experiments on three public malware datasets are exploited to evaluate the effectiveness of the HCMD method using cross validation. Comprehensive experimental results suggest that the HC of a sample extracted by the HCFE approach characterizes the sample more precisely and completely than the GC and LC. The proposed HCMD method outperforms the GC-based and the LC-based malware detection methods in all the experiments for about 1.05% and 0.28% on average, respectively.; EI; CPCI-S(ISTP); ytan@pku.edu.cn; pengtaozhang@gmail.com; June; 140-145; 2015-June
语种	英语
出处	2015 IEEE 28TH CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE)
DOI标识	10.1109/CCECE.2015.7129175
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/423750]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Pengtao,Tan, Ying. Hybrid Concentration Based Feature Extraction Approach for Malware Detection. 2015-01-01.

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