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Intrusion prevention systems: data mining approach

Published:26 February 2010Publication History

ABSTRACT

Host based and network based intrusion prevention systems are available in the market. Host based Intrusion Prevention Systems are designed to protect information systems from unauthorized access, damage or disruption. We combined these features with the network based intrusion systems which counteract the rapidly evolving threats presented by the latest generation of worms, software and network exploits. The raising number of alarms can be reduced by applying data mining algorithms to the network traffic. Our proposed model combines the knowledge discovery and the intrusion detection so that best action can be taken against the attack. Also this knowledge will be helpful to make the systems efficient and secure. The model is useful against denial of services floods, brute force attacks, vulnerability detection, protocols anomaly detection and prevention against unknown exploits. Thus we propose the prevention technology for the security of networks and host users using data mining algorithms. The sequence pattern, classification and association rule mining algorithms are used for taking the various decisions about security.

References

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      cover image ACM Other conferences
      ICWET '10: Proceedings of the International Conference and Workshop on Emerging Trends in Technology
      February 2010
      1070 pages
      ISBN:9781605588124
      DOI:10.1145/1741906

      Copyright © 2010 ACM

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      Publication History

      • Published: 26 February 2010

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