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Author:

Liu, Wei-Wei (Liu, Wei-Wei.) | Shi, Yong (Shi, Yong.) | Guo, Yu (Guo, Yu.) | Han, Zhen (Han, Zhen.) | Shen, Chang-Xiang (Shen, Chang-Xiang.)

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Abstract:

The existing malicious code detection algorithms which are based on individual behaviors have some drawbacks. In this paper we present a new malicious code detection algorithm based on behavior characteristics by importing improved attack tree model to describe the entity relationships during the malicious code execution time. It is named IBC-DA. The experiments result shows that the proposed algorithm works in most cases of detection and only has minor errors in few conditions. This algorithm has very positive sense for unknown malicious code detection.

Keyword:

Signal detection Forestry Trees (mathematics) Viruses Malware

Author Community:

  • [ 1 ] [Liu, Wei-Wei]College of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
  • [ 2 ] [Shi, Yong]College of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
  • [ 3 ] [Guo, Yu]College of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
  • [ 4 ] [Han, Zhen]College of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
  • [ 5 ] [Shen, Chang-Xiang]Beijing University of Technology, Beijing 100124, China

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Source :

Acta Electronica Sinica

ISSN: 0372-2112

Year: 2009

Issue: 4

Volume: 37

Page: 696-700

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: 3

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