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危险理论DCA入侵检测算法中阈值预测的研究

Research on Prediction of Threshold Values in DCA Intrusion Detection Algorithm based on Danger Theory
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摘要 免疫危险理论的最新研究成果是树突状细胞算法(Dendritic Cell Algorithm,DCA).该算法应用在实时入侵检测时具有较优越的性能,该算法通过计算成熟环境抗原值(Mature Context AntigenValue,MCAV)来表示抗原异常度的信息.文章提出了一种基于改进的树突状细胞算法,使算法中的参数其阈值范围可预测,从而能有效的计算成熟环境抗原值表示出模型的异常度.最后通过仿真实验,实验结果表明新算法使树突状细胞算法的异常度量更加精确,算法的检测正确率提高了21.3%~33.5%. The latest research result of artificial immune dangerous theory is Dendritic Cell Algorithm(DCA).The algorithm has more superior performance when being applied in real-time intrusion detection.This algorithm calculates the Mature Context Antigen Value(MCAV) to define abnormal degree.This paper presents an Improved DCA model;the threshold range of algorithm parameters has been predictably controlled.Experimental results show that the new algorithm makes the DCA abnormal measurement more precise and the detection accuracy rate is improved by 21.3%~33.5%.
作者 余剑
出处 《广西民族大学学报(自然科学版)》 CAS 2012年第1期59-62,83,共5页 Journal of Guangxi Minzu University :Natural Science Edition
基金 广西哲学社会科学课题"基于物联网技术的图书馆服务模式研究"(11BTQ001)
关键词 入侵检测 危险理论 树突状细胞算法 成熟环境抗原值 Instruction Detection Danger Theory Dendritic Cell Algorithm Mature Context Antigen Value
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