Universiti Teknologi Malaysia Institutional Repository

Malware detection techniques using artificial immune system

Mohamed Ali, Mohamed Ahmed and Maarof, Mohd. Aizaini (2012) Malware detection techniques using artificial immune system. Lecture Notes In Electrical Engineering, 120 LN . pp. 575-587. ISSN 1876-1100

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Official URL: http://dx.doi.org/10.1007/978-94-007-2911-7_55

Abstract

Using artificial immune system techniques for malware detection has two major benefits. First, increasing the ability to come over some of the traditional detector’s drawbacks, like dealing with the new and polymorphic malware and the increased number of false alarms caused by wrong decision. Second take advantages of the capabilities to learn, adapt, self-tolerance and memories actions, which make it a good example that we can take for solving some major problems in many fields, including the problem of malware detection in computer security which suffering from the rapid increasing in the malware and the problem of false positive alarms. In this paper, we try to highlight the recent techniques applied in malware detection using the artificial immune system from two points of view: self–nonself theory, danger theory.

Item Type:Article
Uncontrolled Keywords:Artificial immune system, Self-nonself theory, danger theory
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Computer Science and Information System
ID Code:47171
Deposited By: Narimah Nawil
Deposited On:22 Jun 2015 05:56
Last Modified:31 Mar 2019 08:34

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