A differential coefficient inspired method for malicious software detection

  • Authors:

  • Liang Yiwen;Yang He;Li Tao;Liu Changdong

  • Affiliations:

  • Computer School, Wuhan University, Wuhan, China;Computer School, Wuhan University, Wuhan, China and Computer School, HuBei University of Education, Wuhan, China;Computer School, Wuhan University, Wuhan, China and College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China;Computer School, Wuhan University, Wuhan, China

  • Venue:
  • IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
  • Year:
  • 2009

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Abstract

Malicious software is one of the most popular security threats of computer networks. It is difficult for traditional solutions to deal with dynamical and variable behaviors against malicious software. Danger Model theory is a hypothesis of Artificial Immune Systems. This hypothesis explains what is malicious from the trend of behaviors in a computer system. This paper presented a novel idea that malicious software is bound to cause changes, and danger signals of Danger Model come from abnormal changes. Staring from monitoring the changes of a computer system, inspired from the principle of differential calculus, a differential coefficient inspired method for malicious software detection is presented, and danger signals can be defined. An example of malicious software is analyzed in this paper, and the result indicated that this method is effective.