Abstract
In this paper, a novel technique for user behavior classification using Fuzzy Rule Based System (FRBS) is proposed. Using this technique, a local area network (LAN) user can be monitored and his/her behavior can be classified depending on his/her activities like unauthorized/disallowed websites usage, attempting to breach in network security by attempting to access the restricted servers, firewalls, unauthorized services access and frequency of attempts etc. The information about a user is obtained by his/her web, database, hardware and other local and network applications logs. FRBS classifies a user to one of the predefined categories based on the information extracted from user logs and prescribed rules. Moreover, Linear Regression (LR) is used to predict the future values of users' behavior based on his/her past behavior/s. Trend line conforms to the actual results. This would great help in network security and privacy as well as users may be guided for sincere mistakes and other measures may be taken by the organization. Significance of the proposed scheme is shown by examples and results.