期刊文献+

量子驱动的克隆选择在入侵检测中的应用 被引量:2

Application of quantum-inspired clonal selection in IDS
下载PDF
导出
摘要 将量子计算技术与克隆选择算法结合,通过对量子编码的检测器进行测量来生成二进制检测器(测量解)在得到的多个测量解中只保存亲和力最高的。既提高了种群多样性避免了早熟,又减少了检测器冗余。在变异过程中,通过对父代检测器和子代检测器进行比较来对变异进行指导,使其向着亲和力更高的方向进行。加快了种群的进化速度。仿真实验表明,同传统克隆选择算法相比,该算法避免了种群进化过程出现的早熟和进化速度慢以及检测器冗余的问题,提高了系统的检测率。 In this paper,the quantum computing technology and the clonal selection is combined.The binary detector(observed solution) is formed by observing the quantum detector.Only the observed solution which has the biggest avidity is preserved.In this way,the prematurity and the detector redundant is avoided.In the process of mutation,the comparison between the progenitor detector and the progeny detector is made for guiding the mutation.It makes the mutation go forward the direction of higher avidity and,the converging speed is improved.Simulation tests show that compared with the traditional clonal selection algorithm the quantum-inspired clonal selection algorithm avoid the problem of prematurity,low converging speed and detector redundant,improving the efficiency of detector optimization.
作者 李岩 张凤斌
出处 《计算机工程与应用》 CSCD 北大核心 2010年第30期112-114,248,共4页 Computer Engineering and Applications
基金 国家自然科学基金No.60671049~~
关键词 克隆选择 检测器 量子驱动 量子编码 clonal selection; detector; quantum-inspired; quantum-code;
  • 相关文献

参考文献6

二级参考文献37

  • 1刘勇,李涛,梁可心.基于动态克隆选择的入侵检测模型[J].计算机工程,2005,31(11):149-150. 被引量:4
  • 2李承祖等.量子通讯和量子计算[M].长沙,国防科技大学出版社,2000
  • 3T Hey.Quantum Computing:An introduction[J].Computing & Control Engineering Journal,1999:105~112
  • 4G W Greenwood.Finding Solutions to NP Problems:Philosophical Differences Between Quantum and Evolutionary Search Algorithms
  • 5周家驹,何险峰译.演化程序-遗传算法和数据编码的结合[M].北京:科学出版社,2000
  • 6T Back,U Hammel,H-P Schwefel.Evolutionary Computation:Comments on the History and Current state[J].IEEE Trans on Neural Networks,1997;1(1):3~17
  • 7R P Feynman.Simulating Physics with Computers.Int J Theor Phys,1982; 21:467~488
  • 8R P Feynman.Quantum Mechanical Computers.Found Phys,1986;16:507~512
  • 9P W Shor.Algorithms for Quantum Computation :Discrete Logarithms and Factoring[C].In:Proceeding of the 35th Annual Symposium on Foundations of Computer Science.1994:20~26
  • 10L K Grover.A Fast Quantum Mechanics Algorithm for Database Search[C].In :Proceedings of the 28th ACM Symposium on Theory of Computation,1996:212~215

共引文献12

同被引文献12

  • 1楚赟,戴英侠,万国龙.一个基于免疫的分布式入侵检测系统模型[J].计算机应用,2005,25(5):1153-1157. 被引量:7
  • 2李涛.基于免疫的网络安全风险检测[J].中国科学(E辑),2005,35(8):798-816. 被引量:40
  • 3Forrest S, Perelson A S, Allen L, et al. Self-nonself discrimi- nation in a computer[ C ]//Proceedings of the IEEE Symposi- um on Research in Security and Privacy. Los Alamos, USA: [ s. n. ] ,1994:202-212.
  • 4Dasgupta D. An Immune Agent Architecture for Intrusion De- tection[ C]//Proc. of GECCO 2000. San Francisco, USA: Morgan Kaufmann Publishers ,2000:42-44.
  • 5Paula F S, Reis M A, Fermandes D A M. A Hybrid IDS Based on the Immune System[ C]//Proc. of the 9th International Conference on Neural Information Processing. Singapore : IEEE Press, 2002 : 1479-1484.
  • 6Kim J, Greensmith J, Twycross J, et al. Malicious Code Execu- tion Detection and Response Immune System Inspired by the Danger Theory[ C ]//Proc. of Adaptive and Resilient Compu- ting Security Workshoo( ARCS-05 ). [ s. 1. ] : F s. n. 1.2005.
  • 7Lee W K, Stolfo S J, Mok K W. A Data Mining Framework for Building Intrusion Detection Models [ C ]//Proc. of 1999 IEEE Symposium on Security and Privacy. Oakland, USA: IEEE Press, 1999.
  • 8肖锋,杨树堂,陆松年,李建华.基于人工免疫的入侵检测模型研究[J].计算机应用与软件,2008,25(2):258-260. 被引量:10
  • 9余航,焦李成,公茂果,杨咚咚.基于正交试验设计的克隆选择函数优化[J].软件学报,2010,21(5):950-967. 被引量:12
  • 10安辉耀,吴泽俊,王新安,王秀云.用于网络入侵检测的群体协同人工淋巴细胞模型[J].通信学报,2010,31(9):122-130. 被引量:7

引证文献2

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部