Volume 12, Issue 3 (Journal of Control, V.12, N.3 Fall 2018)
JoC 2018, 12(3): 63-75 |
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ghazi Z, Doustmohammadi A. Cyber intrusion detection on critical infrastructures using fuzzy neural first order hybrid Petri net . JoC 2018; 12 (3) :63-75
URL: http://joc.kntu.ac.ir/article-1-412-en.html
URL: http://joc.kntu.ac.ir/article-1-412-en.html
1- Amirkabir university
Abstract: (7297 Views)
Due to the growing demand to achieve more secure and reliable systems, development of models, analysis and design of appropriate procedures seems to be necessary. The aim of this paper is designing a controller in order to detect cyber intrusion. In this paper fuzzy neural first order hybrid Petri net is used to design a controller that is capable of detecting cyber intrusions accurately as soon as possible. The stability of the proposed intrusion detection system has been proven for any network conditions and input parameters. To evaluate controller performance, DARPA standard data set is used. The simulation results confirm proper detection rate, low of false positive rate, and also surprisingly high convergence speed.
Keywords: critical infrastructures, cyber attacks, intrusion detection systems, fuzzy neural first order hybrid Petri net.
Type of Article: Research paper |
Subject:
Special
Received: 2016/10/13 | Accepted: 2018/02/12 | Published: 2019/04/28
Received: 2016/10/13 | Accepted: 2018/02/12 | Published: 2019/04/28
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