Decision Tree based Learning Approach for Identification of Operating System Processes

In present scenario various tools like firewalls, anti-virus tool, network security tools, malware removal tools, monitoring tools etc, are being used for providing security to computer systems. Computer security tools available in present era need to be updated and monitored regularly. If any computer users do not regularly update the security tools, such systems will be vulnerable to virus and other attacks. Through this paper a learning system is being proposed to identify the operating system processes as Self and Non-Self, using the concepts of Decision Tree Learning. ID3 algorithm has been used to construct a Decision Tree after calculating the Entropy and Information Gain. Initially Decision Trees are generated using training examples and then these constructed Decision Trees are tested with test data. Further, it has been inferred through experimental results that the Decision Tree Learning approach will provide better security through effective identification of Self and Non-Self