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Neural network approach for intrusion detection

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Published:24 November 2009Publication History

ABSTRACT

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.

References

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  1. Neural network approach for intrusion detection

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                cover image ACM Other conferences
                ICIS '09: Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
                November 2009
                1479 pages
                ISBN:9781605587103
                DOI:10.1145/1655925

                Copyright © 2009 ACM

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                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 24 November 2009

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