期刊文献+

一种基于异常的自适应非选择性算法研究

A self-adaptive negative selection approach for anomaly detection
下载PDF
导出
摘要 本文研究的重点是检测器生成算法,在非选择性变异算法(NegativeSelectionMutation,NSMutation)的基础上,提出了一种自适应非选择性算法,完成了算法的设计、性能分析和实验。实验结果表明,新算法在正确检测、错误检测、计算时间上都表现出优越的性能。 Detector generating algorithms are the emphasis of this research. Based on Negative Selection Mutation algorithm, a new Self-Adaptive Selection algorithm is presented as detectors generating methods. Its design, performance, analysis and experiment is finished. The result of the experiments shows that the new algorithm outperforms the NSMutation in true detections, false detections and computation time.
作者 唐勇 杨华玲
出处 《燕山大学学报》 CAS 2006年第3期247-250,共4页 Journal of Yanshan University
关键词 检测器生成算法 非选择性算法 变异 自适应 detector generating algorithm negative selection algorithm mutation self-adaptive
  • 引文网络
  • 相关文献

参考文献6

  • 1Dasgupta D.An Overview of Artificial Immune Systems and Their Applications[M].Berlin:Springer-Verlag,1999.
  • 2S Forrest,A S Perelson,L Allen,et al..Self-NonselfDiscrimination in a Computer[A].Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy[C],Los Alamitos,1994,202-212.
  • 3D' haeseleer,S Forrest.An immunological approach to change detection:Algorithms,analysis and implications[A].IEEE Symposium on Security and Privacy[C].
  • 4张雅静,单国东.基于生物免疫原理的负选择模式匹配检测算法[J].计算机工程与应用,2004,40(16):15-17. 被引量:4
  • 5吴作顺,窦文华,朱小俊.负选择模型中初始检测器集的一个生成算法[J].电子学报,2003,31(5):687-689. 被引量:3
  • 6Ayara,Timmis,de Lemos,et al..Negative selection:How to generate detectors[A].In Proceeding of ICARIS (International Conference on Artificial Immune System)[C].2002,89-98.

二级参考文献12

  • 1Dasgupta D. An Overview of Artificial Immune Systems and Their Applications [M]. Berlin:Springer-Verlag, 1999.
  • 2J K Percus, O E Percus, A S Perelson. Probability of Sel-Nonself Discrimination [C]. A S Perelson and G Weisbbuch, ed. Theoritical and Experimental Insights into Immunology, NY: Springer-Verlag, 1992. 183- 197.
  • 3P D'haeseleer, S Forrest,P Helman. An Immunological Approach to Change Detection : Algorithms, Analysis, and Implications [ C ]. Proceedings of the 1996 IEEE Symposium on Computer Security and Privacy, 1996.
  • 4R J De Boer, A S Pererson. How Diverse Should the Immune System Be[ C]. Proceedings of the Royal Society London B, v. 252. London:Biol.Sci, 1993. 171 - 175.
  • 5S Forrest, A S Perelson, L Allen R, et al. Self-Nonself Discrimination in a Computer [C]. Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy, Los Alamitos, CA: IEEE Computer Society Press, 1994.
  • 6S Forrest,A S Perelson,L Allen et al.Self-Nonself Discrimination in a Computer[C].In:Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy,Los Alamitos,CA :IEEE Computer Society Press,1994:221~231
  • 7P D'haeseleer,S Forrest,P Helman.A Distributed Approach to Anomaly Detection.http://www.cs.unm.edu/~forrest/publications/negselection97.pdf.1997.12-Oct-2001
  • 8Patrik D'haseleer.An Immunological Approach to Change Detection:Theoretical Results[C].In:The 9th IEEE Computer Security Foundations Workshop,Dromquinna Manor,County Kerry,Ireland,1996:10~12
  • 9Peter J Bentley,Timothy Gordon,Jungwon Kim.New Trends in Evolutionary Computation[C].In:The Congress on Evolutionary Computation (CEC-2001 ),Seoul,Korea,2001;(5):162~169
  • 10Leandro N de Castro,Femando J V Z.Learning and Optimization Using the Clonal Selection Principle[C].In :IEEE Transactions on Evolutionary Computation ,Special Issue on Artificial Immune System,2001

共引文献5

;
使用帮助 返回顶部