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基于熵的实值免疫检测器降维优化算法

Real-valued Immune Detector Dimension-reducing Optimization Algorithm with Entropy
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摘要 针对免疫机制的入侵检测系统中实值检测器的维数灾难问题,借鉴信息熵理论,提出一种基于熵的实值检测器降维优化算法,使检测器在保留足够信息量的前提下在低维空间中运行,有效提高检测效率.实验表明,降维后的检测器表现出更好的检测性能. In order to deal with the ＂dimension curse＂ problem of real-valued detector in immunity-based intrusion detection system,we borrowed ideas from the information entropy theory,and a real-valued immune detector dimension-reducing optimization algorithm is proposed in this paper.The optimized detectors can retain the most useful information and work in the low-dimensional shape-space,which can improve the detection efficiency.The experiments show that the dimension-reduced detectors have better detector performances.
作者 孙永倩 席亮
机构地区 哈尔滨理工大学计算机科学与技术学院
出处 《哈尔滨理工大学学报》 CAS 2014年第2期68-72,共5页 Journal of Harbin University of Science and Technology
基金 国家自然科学基金(61103149)
关键词 人工免疫 入侵检测 检测器 降维 熵 artificial immune intrusion detection detector dimension-reducing entropy
分类号 TP393.0 [自动化与计算机技术—计算机应用技术]
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参考文献20

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二级参考文献45

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哈尔滨理工大学学报
2014年 第2期

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