Network Intrusion Detection System Using Genetic Algorithm and Fuzzy Logic
Mostaque Md. Morshedur Hassan
Assistant Professor, Department of Computer Science and IT, Lalit Chandra Bharali College, Guwahati, India
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These days Intrusion Detection System (IDS) which is defined as a solution of system security is employed to identify the abnormal activities in a computer system or network. So far different approaches have been utilized in intrusion detections, but unluckily any of the systems is not entirely ideal. Hence, the hunt of improved method goes on. In this progression, here I have designed an Intrusion Detection System (IDS), by applying genetic algorithm (GA) and fuzzy logic to efficiently detect various types of the intrusive activities within a network. The proposed fuzzy logic-based system could be able to detect the intrusive activities of the computer networks as the rule base holds a better set of rules. The experiments and evaluations of the proposed intrusion detection system are performed with the KDD Cup 99 intrusion detection benchmark dataset. The experimental results clearly show that the proposed system achieved higher accuracy rate in identifying whether the records are normal or abnormal ones and obtained reasonable detection rate.