Enhancing collaborative intrusion detection networks against insider attacks using supervised intrusion sensitivity-based trust management model
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- 作者：Wenjuan Lia ; wenjuan.li@my.cityu.edu.hk" class="auth_mail" title="E-mail the corresponding author ; Weizhi Mengb ; yuxin.meng@my.cityu.edu.hk" class="auth_mail" title="E-mail the corresponding author ; Lam-For Kwoka ; cslfkwok@cityu.edu.hk" class="auth_mail" title="E-mail the corresponding author ; Horace H.S. IPa ; cship@cityu.edu.hk" class="auth_mail" title="E-mail the corresponding author
- 关键词：Intrusion detection ; Collaborative network ; Intrusion sensitivity ; Machine learning ; Trust management model ; Insider attacks
- 刊名：Journal of Network and Computer Applications
- 出版年：2017
- 出版时间：1 January 2017
- 年：2017
- 卷：77
- 期：Complete
- 页码：135-145
- 全文大小：1246 K
文摘
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We proposed a supervised learning approach to help automatically allocate the values of intrusion sensitivity.
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We compared the performance of three supervised classifiers in allocating sensitivity values.
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We evaluated our approach under both simulated and real environments.