IMPROVING SECURITY BY PREDICTING ANOMALY USER THROUGH WEB MINING: A REVIEW
Mahesh Malviya, Abhinav Jain, Neetesh Gupta · 2011
The web log data embed much of the user’s browsing behavior. Every visit of internet user is recorded in web server log. There are many systems that attempt to predict user navigation on the internet through the use of past behavior, preferences and environmental factors. Ensuring the integrity of computer networks, both in relation to security and with regard to the institutional life of the nation in general, is a growing concern. Security and defense networks, proprietary research, intellectual property, and data based market mechanisms that depend on unimpeded and undistorted access, can all be severely compromised by malicious intrusions. We need to find the best way to protect these systems. In addition we need techniques to detect security breaches. There has been much interest on using data mining for counter-terrorism and cyber security applications. For example, data mining can be used to detect unusual patterns, terrorist activities and fraudulent behavior. In addition data mining can also be used for intrusion detection and malicious code detection. Our current research is focusing extensively for intrusion detection.