eprintid: 1208 rev_number: 2 eprint_status: archive userid: 1 dir: disk0/00/00/12/08 datestamp: 2023-11-09 15:49:22 lastmod: 2023-11-09 15:49:22 status_changed: 2023-11-09 15:39:13 type: conference_item metadata_visibility: show creators_name: Ahmad, I. creators_name: Abdullah, A.B. creators_name: Alghamdi, A.S. title: Comparative analysis of intrusion detection approaches ispublished: pub keywords: Artificial Neural Network; Detection rates; Intrusion detection approaches; Intrusion detection systems; Multi-criteria, Computer crime; Computer simulation; Decision making; Neural networks, Intrusion detection note: cited By 7; Conference of 12th UKSim International Conference on Modelling and Simulation, UKSim 2010 ; Conference Date: 24 March 2010 Through 26 March 2010; Conference Code:80938 abstract: Information security is a serious issue especially in present age because a solo attack may cause a big harm in computer and network systems. Several intrusion detection approaches exist to tackle this critical issue but the problem is which one is more suitable in the field of intrusion. Further, these approaches are used in intrusion detection systems. Therefore, in this paper, we evaluated them so that a suitable approach may be advised to intrusion detection systems. This work describes the concepts, tool and methodology being used for evaluation analysis of different intrusion detection approaches using multi-criteria decision making technique. Moreover, conclusion on results is made and direction for future works is presented. © 2010 IEEE. date: 2010 official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954516892&doi=10.1109%2fUKSIM.2010.112&partnerID=40&md5=6efb3666af6eda2fe0a240d56cd2f450 id_number: 10.1109/UKSIM.2010.112 full_text_status: none publication: UKSim2010 - UKSim 12th International Conference on Computer Modelling and Simulation place_of_pub: Cambridge pagerange: 586-591 refereed: TRUE isbn: 9780769540160 citation: Ahmad, I. and Abdullah, A.B. and Alghamdi, A.S. (2010) Comparative analysis of intrusion detection approaches. In: UNSPECIFIED.