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Author:

Lai, Ying-Xu (Lai, Ying-Xu.) (Scholars:赖英旭) | Liu, Hong-Nan (Liu, Hong-Nan.) | Yang, Zhen (Yang, Zhen.) (Scholars:杨震) | Liu, Jing (Liu, Jing.)

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Abstract:

To overcome the shortcoming of traditional methods in feature extraction, unknown malicious codes detection based on the Lempel-Ziv-Welch(LZW) compression algorithm was proposed. The strings were extracted from file character flow. The length of strings was not over a thredhold. Then, compression dictionaries of normal code and malicious code were built by extracted strings. To detect unknown malicious codes, the normal code dictionary and malicious code dictionary were used to compress a tested file and two different compression ratios were obtained. According to the minimum description length(MDL) theory, the authors compared the two compression ratios and classified the tested file into the class in which got better compression ratio. Experimental results show that the method of unknown malicious code detection based on LZW compression algorithm has a good effect.

Keyword:

Codes (symbols) Feature extraction Malware

Author Community:

  • [ 1 ] [Lai, Ying-Xu]College of Computer Science, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Liu, Hong-Nan]College of Computer Science, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Yang, Zhen]College of Computer Science, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Liu, Jing]College of Computer Science, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2012

Issue: 7

Volume: 38

Page: 1087-1092

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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