Anomaly detection system: Towards a framework for enterprise log management of security services

In recent years, enterprise log management systems have been widely used by organizations. Several companies such as (IBM, MacAfee and Splunk etc.) have brought their own log management solutions to the market. However, the problem is that these systems often require proprietary hardware and do not involve web usage mining to analyze the log data. The purpose of this paper is to investigate an approach towards a framework for managing security logs in enterprise organizations called of the anomaly detection system (ADS), built to detect anomalous behavior inside computer networks that is free from hardware constraints and benefits from web usage mining to extract useful information from the log files.

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