Internet provides huge information and value to the users but at the same time access to the internet is prone to increasing number of attacks. Due to vulnerabilities in the network system, protecting network from malicious activities is prime concern today. Tracing the source of the attacking packet is very difficult because of stateless and destination based routing infrastructure of Internet. If the attacks are detected successfully, then preventive measures for attacks can be taken. Intrusion prevention systems are designed based on the assumption that the behaviour of an intruder is different from a normal user. This paper describes the information sources for intrusion-detection. Combined features of network based intrusion systems and statistical data correlation techniques counteract the rapidly evolving threats presented by the latest generation of worms, software and network exploits. We propose an intrusion prevention model incorporating features of intrusion detection, prevention and data mining with data correlation.

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Network Security Attacks Intrusion Prevention