Research on application of intrusion detection system in data mining

Network security is a large and growing area of concern for every network. The more we invent for the good of humanity, humans try to negate the good factor and hence the fear of viruses and hacking. Research has to move in the direction of preserving and guarding network environments which today are facing an ever increasing number of security threats in the form of Trojan worm attacks and viruses that can damage the Computer systems and communication channel. Firewalls are used as a security check point in a network environment; nevertheless there are still various types of security issues which are on the rise. In order to strengthen the network from illegal access the concept of IDS (Intrusion Detection System) is gaining popularity around the world. The applications of the data mining in the computer security field improves the development of IDS in order to work on these applications it is essential to classify the degree of attacks in IDS and use it through data mining. Despite the use of IDS we cannot be completely certain about its workability and results of IDS use have been uncertain. To plug the loopholes we need to adjust the detection strategy according to the degree of attack activities to ensure error free results.