吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (2): 568-577.doi: 10.13229/j.cnki.jdxbgxb201602035

• Orginal Article • Previous Articles     Next Articles

High dimensional differential evolutionary algorithm based on cloud population for network security prediction

HU Guan-yu, QIAO Pei-li   

  1. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China
  • Received:2014-04-15 Online:2016-02-20 Published:2016-02-20

RICH HTML

0   

PDF (PC)

332

Abstract: A novel differential evolutionary algorithm based on could population (CPDE) is proposed to solve the network security situation prediction. The proposed concepts of cloud population and the distribution chain promote the diversity of the population. In this algorithm, first, the intrusion operator is employed to introduce the competition among the cloud populations, where the winners will implant their distribution into other cloud individuals. Then, cooperative operator is used to introduce the collaboration among the cloud individuals and perform the differential operation. Finally, the accuracy of the algorithm is improved using the local search operator. Experiment results show that the proposed CPDE is an efficient high-dimensional evolutionary algorithm and possesses certain advantages in optimizing the prediction model of the network security.

Key words: computer application technology, differential evolutionary algorithm, cloud model, cloud population, distribution chain, network security situation prediction

CLC Number: 

  • TP18
[1] 张晓伟, 刘三阳, 迟晓妮. 高效求解多峰值全局优化的区间-遗传算法[J]. 吉林大学学报:工学版,2008, 38(4): 876-879.
Zhang Xiao-wei, Liu San-yang, Chi Xiao-ni. Efficient interval-genetic algorithm for multi-peak global optimization[J]. Journal of Jilin University (Engineering and Technology Edition),2008, 38(4): 876-879.
[2] 朝勇, 郑建国. 用于高维函数优化的多智能体量子进化算法[J]. 自然科学进展,2007, 18(2): 197-205.
Chao Yong, Zheng Jian-guo. A multi-agent quantum evolutionary algorithm for the high dimensional function optimization[J]. Progress in Natural Science,2007, 18(2): 197-205.
[3] Noman N, Iba H. Enhancing differential evolution performance with local search for high dimensional function optimization[C]//Genetic and Evolutionary Computation Conference (GECCO),2005: 967-974.
[4] Zhang Wei-guang, He Rui, Liu Yu, , et al. An evolutionary algorithm based on cloud model[J]. Chinese Journal of Computers,2008, 31(7): 1082-1091.
[5] Dai Chao-hua, Zhu Yun-fang, Chen Wei-rong, et al. Cloud model based genetic algorithm and it's applications[J]. Acta Electronica Sinica,2007, 35(7): 1419-1424.
[6] Dai Chao-hua, Zhu Yun-fang, Chen Wei-rong. Adaptive genetic algorithm based on cloud theory[J]. Control Theory and Applications,2007, 24(4): 646-650.
[7] Li De-yi, Meng Hai-jun, Shi Xue-mei. Membership clouds and membership cloud generators[J]. Journal of Computer Research Development, 1995, 32(6): 15-20.
[8] Storn R , Price K. Differential evolution-A simple and efficient adaptive scheme for global optimization over continuous spaces[R]. Berkeley: University of California , 2006.
[9] Lampinen J. A bibliography of differential evolution algorithm[EB/OL]. http://www. lut .fi/~jlampine/ debiblio. Htm,2002-10-14.
[10] 李德毅, 杜鹢. 不确定性人工智能[M]. 北京:国防工业出版社,2005.
[11] Andries P Engelbrecht. Computational Intelligence: An Introduction[M].2nd Edition. Beijing:Tsinghua University Press, 2010.
[12] Yao X, Lin G, Liu Y. An analysis of evolutionary algorithms based on neighbourhood and step size[C]//Proceedings of the Sixth Annual Conference on Evolutionary Programming, 1997:297-307.
[13] Yao X, Liu Y, Lin G. Evolutionary programming made faster[J]. IEEE Transactions on Evolutionary Computation, 1999, 3(2):82-102.
[14] Nikolaus H. The CMA Evolution Strategy: A Comparing Review Towards a New Evolutionary Computation[M]. Berlin: Springer, 2006:75-102.
[15] Storn R, Price K. Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces[J]. Journal of Global Optimization, 1997, 11(4):341-359.
[16] Kennedy J, Eberhart R C. Particle swarm optimization[C]//Proceedings of the 1995 IEEE International Conference on Neural Networks, Piscataway, NJ: IEEE Service Center, 1995:1942-1948.
[17] BASS T. Intrusion detection system and multi-sensor data fusion: creating cyberspace situation awareness[J]. Communications of The ACM, 2000, 43(4): 99-105.
[18] 王慧强, 赖积保, 胡明明, 等. 网络安全态势感知关键技术研究[J]. 武汉大学学报:信息科学版, 2008, 33(10): 995-998.
Wang Hui-qiang, Lai Ji-bao, Hu Ming-ming, et al. Research on key technologies for implementing network security situation awareness[J]. Geomatics and Information Science of Wuhan University, 2008, 33(10): 995-998.
[19] 任伟,蒋兴浩,孙锬锋. 基于RBF神经网络的网络安全态势预测方法[J]. 计算机工程与应用, 2006, 31: 136-139.
Ren Wei, Jiang Xing-hao, Sun Tan-feng. RBFNN-based prediction of network security situation[J].Computer Engineering and Application,2006, 31: 136-139.
[20] 陈秀真, 郑庆华, 管晓宏, 等. 层次化网络安全威胁态势量化评估方法[J]. 软件学报, 2006, 17(4): 885-897.
Chen Xiu-zhen, Zheng Qing-hua, Guan Xiao-hong, et al. Quantitative hierarchical threat evaluation model for network security[J]. Journal of Software, 2006, 17(4): 885-897.
[1] HU Guan-yu, QIAO Pei-li. Chaos covariance matrix adaptation evolution strategy optimization algorithm [J]. 吉林大学学报(工学版), 2017, 47(3): 937-943.
[2] LIU Xing-cai, HE Shi-wei, SUN Yang, LI Hao-dong, JING Yun. Comprehensive transportation mixed network design and freight flow allocation based on cloud harmony search algorithm [J]. 吉林大学学报(工学版), 2016, 46(1): 108-113.
[3] ZHOU Ji-biao, CHEN Hong, YAN Bin, ZHANG Wen, FENG Wei. Identification of pedestrian crowding degree in metro transfer hub based on normal cloud model [J]. 吉林大学学报(工学版), 2016, 46(1): 100-107.
[4] TONG Jin, WANG Ya-hui, FAN Xue-mei, ZHANG Shu-jun, CHEN Dong-hui. Monitoring system of cold chain logistics for farm fresh produce [J]. 吉林大学学报(工学版), 2013, 43(06): 1707-1711.
[5] JING Yun, HE Shi-wei, SONG Rui, LI Hao-dong. Dynamic empty car scheduling optimization based on immune clonal with cloud preference [J]. 吉林大学学报(工学版), 2012, 42(增刊1): 261-265.
[6] YANG Zhi-xiao, FAN Yan-feng, SUN Fu-yan. Uncertainty control based on normal cloud model for nodding actions of virtual human [J]. 吉林大学学报(工学版), 2012, 42(02): 476-482.
[7] Zhang Jun；Zhang Guo-ying；Liu Yu-shu. Network anomaly detection based on attributes similarity and cloud model [J]. 吉林大学学报(工学版), 2006, 36(06): 954-0957.
[8] Duan Hai-bin, Wang Dao-bo, Yu Xiu-fen . MAXMIN meeting ant colony algorithm based on cloud model
theory and niche ideology [J]. 吉林大学学报(工学版), 2006, 36(05): 803-0808.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd