Title :
An application model of intrusion detection based on incremental data mining
Author :
Zhang, Yun ; Yang, Binwei
Author_Institution :
Dept. of Comput. Eng., ZheJiang Inst. of Mech. & Electr. Eng., Hangzhou, China
Abstract :
Facing all kinds of attacks and destruction of campus network, we urgently need a good detection model to detecting all kinds of campus network attack with high detection rate and low false positive rate, which possesses the ability of recognizing unknown abnormal activities. With considering the characteristic of network data source, a new intrusion detection application model is proposed. With the adaptive learning ability,this application model can fast recognize normal or abnormal activities of the campus network and possess the basic ability of recognizing new and unknown abnormal activities.
Keywords :
computer network security; educational administrative data processing; adaptive learning ability; campus network attack; incremental data mining; intrusion detection application model; Adaptation models; Computational modeling; Computers; Conferences; Data mining; Data models; Intrusion detection; Application model; Incremental data mining; Intrusion detection;
Conference_Titel :
Computer Science and Service System (CSSS), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9762-1
DOI :
10.1109/CSSS.2011.5972070