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Intrusion Detection System using Hidden Markov Model (HMM)

Intrusion detection systems play a key role in detecting such malicious activities and enable administrators in securing network systems. Intrusion detection can detect malicious attacks that have penetrated preventative mechanisms such as firewalls, which can help provide damage assessment, response and prosecution support. This paper describes a novel approach using Hidden Markov Models (HMM) to detect Internet attacks. In this paper we describe an intrusion detection system for detection of signature based attack. These attack signatures encompass specific traffic or activity that is based on known intrusive activity. We performed single and multiple HMM model for source separation both on IP and port information of source and destination. This approach reduced the false positive rate and we made this type of source separation as our basic step for building HMM.