期刊名称：International Journal of Reviews in Computing
印刷版ISSN：2076-3328
电子版ISSN：2076-3336
出版年度：2014
卷号：13
出版社：Little Lion Scientific Research and Developement
摘要：Wireless Sensor Network is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the network. It is widely known, that the intrusion detection is one of the most efficient security mechanisms to protect the network against malicious attacks or unauthorized access. In this paper, we propose a hybrid intrusion detection system for clustered WSN. Our intrusion framework uses a machine learning approach based Incremental Support vector machine (ISVM). it can overcome the shortages of SVM-time-consuming of training and massive dataset storage and detect unseen or unknown attack.
关键词：Data Mining; Rough Set Theory; Support Vector Machine; Attack; Intrusion Detection System
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