Firewall Design: Consistency, Completeness, and Compactness
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
On scalable attack detection in the network
IEEE/ACM Transactions on Networking (TON)
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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.