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multiple-attacks-classification
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Web Anomaly Host-Based IDS, Using Computational Intelligence Approach
, M.Sc. Thesis Sharif University of Technology ; Azmi, Reza (Supervisor)
Abstract
In this thesis we propose a two-layer hybrid fuzzy genetic algorithm for designing anomaly based an Intrusion Detection System. Our proposed algorithm is based on two basic Genetic Based Machine Learning Styles (i.e. Pittsburgh and Michigan). The Algorithm supports multiple attack classifications; it means that the algorithm is able to detect five classes of network patterns consisting of Denial of Service, Remote to Local, User to Root, Probing and Normal class.
Our proposed algorithm has two approaches. In the first approach we choose Pittsburgh style as the base of the algorithm that provides a global search. Then combine it with Michigan style to support local search. In this...
Our proposed algorithm has two approaches. In the first approach we choose Pittsburgh style as the base of the algorithm that provides a global search. Then combine it with Michigan style to support local search. In this...
IDuFG: Introducing an intrusion detection using hybrid fuzzy genetic approach
, Article International Journal of Network Security ; Volume 17, Issue 6 , 2015 , Pages 754-770 ; 1816353X (ISSN) ; Azmi, R ; Sharif University of Technology
Femto Technique Co., Ltd
2015
Abstract
In this paper, we propose a hybrid approach for designing Intrusion Detection Systems. This approach is based on a Fuzzy Genetic Machine Learning Algorithm to generate fuzzy rules. The rules are able to solve the classification problem in designing an anomaly IDS. The proposed approach supports multiple attack classification. It means that, it is able to detect five classes consist of Denial of Service, Remote to Local, User to Root, Probing and normal classes. We present a two-layer optimization approach based on Pittsburgh style and then combine it with Michigan style. To improve the performance of the proposed system, we take advantages of memetic approach and proposed an enhanced version...