A novel signature searching for Intrusion Detection System using data mining

Intrusion Detection System (IDS) has recently emerged as an important component for enhancing information system security. Data mining and machine learning technology has been extensively applied in network intrusion detection and prevention systems by discovering user behavior patterns from the network traffic data. In this paper, we propose a novel signature searching to detect intrusion based on data mining, which is an improved Apriori algorithm. We evaluate the capability of this new approach with the data from KDD 1999 data mining competition. Our experimental results demonstrate the potential of the proposed method.