An Approach to Understand the End User Behavior through Log Analysis

Abstract

Categorizing the end user in the web environment is a mindnumbing task. Huge amount of operational data is generated when end user interacts in web environment. This generated operational data is stored in various logs and may be useful source of capturing the end user activates. Pointing out the suspicious user in a web environment is a challenging task. To conduct efficient investigation in cyber space the available logs should be correlated. In this paper a prototype system is developed and implemented which is based on relational algebra to build the chain of evidence. The prototype system is used to preprocess the real generated data from logs and classify the suspicious user based on decision tree. At last various challenges in the logs managements are presented.