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Dr. Assoc. Prof. Ahmad Taher Azar :: Publications:

Title:
Continuous Features Discretizaion for Anomaly Intrusion Detectors Generation. The 17th Online World Conference on Soft Computing in Industrial Applications (WSC17), December 10 - 21, 2012.
Authors: Amira Sayed A.Aziz, Ahmad Taher Azar, Aboul Ella Hassanien, Sanaa Al-Ola Hanafy
Year: 2012
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link:
Full paper Ahmad Taher Azar_online_wsc17_submission_55.pdf
Supplementary materials Not Available
Abstract:

Network security is a growing issue, with the evolution of computer systems and expansion of attacks. Biological systems have been inspiring scientists and designs for new adaptive solutions, such as genetic algorithms. In this paper, an approach that uses the genetic algorithm to generate anomaly network intrusion detectors is used. An algorithm is proposed using a discretization method for the continuous features selection of intrusion detection, to create some homogeneity between values, which have different data types. Then, the intrusion detection system is tested against the NSL-KDD data set using different distance methods. A comparison is held amongst the results, and it is shown by the end that this proposed approach has good results, and recommendations are given for future experiments.

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