The Power of Temporal Pattern Processing in Anomaly Intrusion Detection

Abstract— A clear deficiency in most of todays Anomaly Intrusion Detection Systems (AIDS) is their inability to distinguish between a new form of legitimate normal behavior and a malicious attack based on known previous normal behaviors. This deficiency is known as the lack of generalization ability. The lack of generalization ability of the present AIDS results mainly in two direct consequences. As a first consequence, the current AIDS are capable of detecting neither new sophisticated attacks nor slight variations of known attacks launched against computing systems. The high rate of false positive and false negative alerts generated by the current AIDS is the second consequence. Many research initiatives that utilize machine learning techniques including neural networks have been proposed to overcome the lack of generalization. Unfortunately, most of such research initiatives have intrinsically focused on utilizing static techniques, that perform structural pattern recognition. ...

• Type: Conference
• Year: 2007
• Where: ICC
• Authors: Mohammad Al-Subaie, Mohammad Zulkernine
• Keywords: Communications, Current Aids, ICC 2007, Neural Network, Normal Behaviors