Intelligence Intrusion Detection Prevention Systems (IDPs) have played an important role to defend our networks from malware attacks. However, since they are still unable to detect an unknown attack, i.e. the zero-day attack, the ultimate challenge in the intrusion detection field is how we can exactly identify such an attack. This paper presents a novel approach which differs from the traditional detection models that are based on intelligence. The proposed method can extract unknown activities from IDS alerts by applying data mining technique.
BT - Information & Security: An International Journal DA - 2013 IS - 2 LA - eng N2 -Intelligence Intrusion Detection Prevention Systems (IDPs) have played an important role to defend our networks from malware attacks. However, since they are still unable to detect an unknown attack, i.e. the zero-day attack, the ultimate challenge in the intrusion detection field is how we can exactly identify such an attack. This paper presents a novel approach which differs from the traditional detection models that are based on intelligence. The proposed method can extract unknown activities from IDS alerts by applying data mining technique.
PY - 2013 SE - 109 SP - 109 EP - 119 T2 - Information & Security: An International Journal TI - Intelligent Intrusion Detection Prevention Systems VL - 26 ER -