Data mining for network intrusion detection system in real time
Intrusion detection technology is an effective approach to dealing with the problems of network security. In this paper, we
present a data mining-based network intrusion detection framework in real time (NIDS). This framework is a distributed
architecture consisting of sensor, data preprocessor, extractors of features and detectors. To improve efficiency, our approach
adopts a novel FP-tree structure and FP-growth mining method to extract features based on FP-tree without candidate generation.
Keywords: data mining, FP-growth, intrusion detection, network, real time
Citation: *, ( 2015), Data mining for network intrusion detection system in real time. Scientific Transactions in Environment and Technovation Journal(STET), 3(2): 74-78
Received: 2016-05-11 06:48:46; Accepted: 2016-05-11 06:48:55;