Work place: Islamic Azad University, Shabestar Branch, Shabestar, Iran
E-mail: e.moradpoormail@yahoo.com
Website:
Research Interests: Computer systems and computational processes, Artificial Intelligence, Computer Architecture and Organization, Systems Architecture, Intrusion Detection System, Data Structures and Algorithms
Biography
Ezzat Moradpour was born in 1982. He received the B.S. degree in software engineering from Payamenour University in 2006 and M.S. degree in software engineering from Islamic Azad University in 2012. His research interest includes intrusion detection systems and artificial intelligence.
By Zahra Atashbar Orang Ezzat Moradpour Ahmad Habibizad Navin Amir Azimi Alasti Ahrabi Mir Kamal Mirnia
DOI: https://doi.org/10.5815/ijcnis.2012.11.04, Pub. Date: 8 Oct. 2012
By ever increase in using computer network and internet, using Intrusion Detection Systems (IDS) has been more important. Main problems of IDS are the number of generated alerts, alert failure as well as identifying the attack type of alerts. In this paper a system is proposed that uses Adaptive Neuro-Fuzzy Inference System to classify IDS alerts reducing false positive alerts and also identifying attack types of true positive ones. By the experimental results on DARPA KDD cup 98, the system can classify alerts, leading a reduction of false positive alerts considerably and identifying attack types of alerts in low slice of time.
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