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Author:

Lai, Y. (Lai, Y..) | Liu, Z. (Liu, Z..)

Indexed by:

Scopus

Abstract:

It is very difficult to improve Bayesian classifier detection accuracy because selected features are not completely independent In this paper, unknown malicious code detection based on encoding is proposed according Minimum Description Length (MDL) principle. We use encoding module instead of the conditional independence assumption and statistical classification method. The experiment results show our method is efficient. ©2012 International Information Institute.

Keyword:

Bayesian algorithm; Detection; Lzw compression algorithm; Malicious codes

Author Community:

  • [ 1 ] [Lai, Y.]College of Computer Science, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Liu, Z.]Science and Technology Engineering Faculty, Beijing Vocational College of Electronic Science, Beijing 100029, China

Reprint Author's Address:

  • [Lai, Y.]College of Computer Science, Beijing University of Technology, Beijing 100124, China

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Information

ISSN: 1343-4500

Year: 2012

Issue: 11 A

Volume: 15

Page: 4563-4571

Language: English

JCR Journal Grade:4

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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