Research on the intrusion detection technology with hybrid model
Qingqing Zhang, Hongbian Yang, Li Kai, Qian Zhang
Abstract
Qingqing Zhang, Hongbian Yang, Li Kai, Qian Zhang
Abstract
Intrusion Detection is an indispensable component of Network Security. Because exists the problems of the high false positives rate and low detection efficiency in the current intrusion detection system, in this paper, we propose a hybrid intrusion detection model and improve intrusion detection system analyzer, applying the Data fusion and data mining techniques to intrusion detection systems. We have researched this model further more and analyzed its architecture in detail.
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Intrusion Detection is an indispensable component of Network Security. Because exists the problems of the high false positives rate and low detection efficiency in the current intrusion detection system, in this paper, we propose a hybrid intrusion detection model and improve intrusion detection system analyzer, applying the Data fusion and data mining techniques to intrusion detection systems. We have researched this model further more and analyzed its architecture in detail.
Key concepts: Intrusion detection system, Computer science, False positive paradox, Anomaly-based intrusion detection system, Data mining, Component (thermodynamics), Network security, Host-based intrusion detection system