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Full Version: Analysis of Hybrid Soft Computing Techniques for Intrusion Detection on Network
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Analysis of Hybrid Soft Computing Techniques for Intrusion Detection on Network

Abstract

Intrusion detection is an action towards security of a network when a system or network is being used inappropriately or without authorization. The use of Soft Computing Approaches in intrusion detection is an Appealing concept for two reasons: firstly, the Soft Computing Approaches achieve tractability, robustness, low solution cost, and better report with reality. Secondly, current techniques used in network security from intrusion are not able to cope with the dynamic and increasingly complex nature of network and their security. It is hoped that Soft Computing inspired approaches in this area will be able to meet this challenge. Here we analyze the approaches including the examination of efforts in hybrid system of SC such as neuro-fuzzy, fuzzy-genetic, neuro-genetic, and neuro-fuzzy-genetic used the development of the systems and outcome their implementation. It provides an introduction and review of the key developments within this field, in addition to making suggestions for future research.