Anomaly Based Intrusion Detection Using Data Mining and String Metrics

Computer systems and networks are subject to electronic attacks with increasing number and severity. Intrusion detection is an important technology in the contemporary world as well as an active area of research. The present paper introduces an adaptive approach of data mining techniques and string metrics in anomaly based intrusion detection systems. The conducted simulation experiments and represented results substantiate the proposed method produces reliable results while monitoring the protected system and alarming the detected attacks.