Intrusion Detection System is based on the belief that an intruder's behavior will be noticeably different from that of a legitimate user and would exploit security vulnerabilities. This paper proposes a neural network approach to improve the alert throughput of a network and making it attack prohibitive using IDS. For evolving and testing intrusion the KDD CUP 99 dataset are used. The result of proposed approach is found to be more efficient in the area of Intrusion Detection and promises a good scope for further research.
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