Idris, Norbik Bashah and Bharanidhran, Shanmugam (2005) Artificial intelligence techniques applied to intrusion detection. In: Proceedings of INDICON 2005: An International Conference of IEEE India Council. IEEE, pp. 52-55.
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Official URL: http://dx.doi.org/10.1109/INDCON.2005.1590122
Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection. The techniques that are being investigated includes neural networks and fuzzy logic with network profiling, that uses simple data mining techniques to process the network data. The proposed system is a hybrid system that combines anomaly, misuse and host based detection. Simple Fuzzy rules, allow us to construct if-then rules that reflect common ways of describing security attacks. For host based intrusion detection we use neural-networks along with self organizing maps. Suspicious intrusions can be traced back to their original source path and any traffic from that particular source will be redirected back to them in future. Both network traffic and system audit data are used as inputs for both
|Item Type:||Book Section|
|Additional Information:||INDICON 2005: An International Conference of IEEE India Council; Chennai; 11 December 2005 through 13 December 2005|
|Uncontrolled Keywords:||data mining, fuzzy logic, intrusion detection, network security|
|Subjects:||T Technology > T Technology (General)|
T Technology > TJ Mechanical engineering and machinery
|Deposited By:||S.N.Shahira Dahari|
|Deposited On:||31 May 2011 01:20|
|Last Modified:||31 May 2011 01:20|
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