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Erschienen in:
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2012 | OriginalPaper | Buchkapitel

55. Malware Detection Techniques Using Artificial Immune System

verfasst von : Mohamed Ahmed Mohamed Ali, Mohd Aizaini Maarof

Erschienen in: Proceedings of the International Conference on IT Convergence and Security 2011

Verlag: Springer Netherlands

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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.

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Metadaten
Titel
Malware Detection Techniques Using Artificial Immune System
verfasst von
Mohamed Ahmed Mohamed Ali
Mohd Aizaini Maarof
Copyright-Jahr
2012
Verlag
Springer Netherlands
Buch
Proceedings of the International Conference on IT Convergence and Security 2011

Print ISBN: 978-94-007-2910-0

Electronic ISBN: 978-94-007-2911-7

Copyright-Jahr: 2012

DOI
https://doi.org/10.1007/978-94-007-2911-7_55

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