计算机科学 ›› 2013, Vol. 40 ›› Issue (11): 108-111.

• 信息安全 • 上一篇    下一篇

基于IHS_RELM的网络安全态势预测方法

陈虹,王飞,肖振久   

  1. 辽宁工程技术大学软件学院 葫芦岛125105;辽宁工程技术大学软件学院 葫芦岛125105;辽宁工程技术大学软件学院 葫芦岛125105
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(61103199)资助

Method of Network Security Situation Prediction Based on IHS_RELM

CHEN Hong,WANG Fei and XIAO Zhen-jiu   

  • Online:2018-11-16 Published:2018-11-16

摘要: 针对网络安全态势感知中的态势预测问题,提出一种基于IHS_RELM的网络安全态势预测方法。对和声搜索算法的原理进行了研究,在此基础上提出一种改进的和声搜索算法。将正则极速学习机(RELM)嵌入到改进的和声搜索算法(IHS)的目标函数计算过程中,利用IHS算法的全局搜索能力来优化选取RELM的输入权值和隐含层阈值,在一定程度上提升了RLLM的学习能力和泛化能力。仿真实验表明,与已有的其他预测方法相比,该方法具有更好的预测效果。

关键词: 和声搜索算法,正则极速学习机,网络安全态势预测,参数优化

Abstract: To address the situation prediction problem in the network security situation awareness,this paper presented a prediction method of network security situation based on the algorithm of HIS_RELM. We proposed an improved harmony search(IHS) algorithm after studying the principle of the harmony search(HS) algorithm.This method embeds the regularized extreme learning machine(RELM) in the process of the objective function calculation of the improved harmony search algorithm,and takes advantage of the global searching ability of the IHS algorithm to optimize the input weights and hidden layer threshold of the RELM.To some extent,this enhances the learning ability and generalization ability of the RELM.Simulation experiments show that this method has better prediction affection in comparison with other existing prediction methods.

Key words: Harmony search algorithm(HS),Regularized extreme learning machine(RELM),Network security situation prediction,Parameters optimization

[1] Zhang Song-mei,Yao Shan,Ye Xin’en,et al.A Network Security Situation Analysis Framework Based on Information Fusion[C]∥Information Technology and Artificial Intelligence Conference(ITAIC).20116th IEEE Joint International.2011,1:326-332
[2] 韩敏娜,刘渊,陈烨.基于集对分析的网络安全态势评估[J].计算机应用研究,2012,29(10):3824-3827
[3] 孟锦,马驰,何加浪,等.基于HHGA-RBF神经网络的网络安全态势预测模型[J].计算机科学,2011,38(7):71-75
[4] 尤马彦,凌捷,郝彦军.基于Elman神经网络的网络安全态势预测方法[J].计算机科学,2012,9(6):61-76
[5] 王晋东,沈柳青,王坤,等.网络安全态势预测及其在智能防护中的应用[J].计算机应用,2010,30(6):1480-1488
[6] 邓万宇,郑庆华,陈琳,等.神经网络极速学习方法研究[J].计算机学报,2010,33(2):279-287
[7] Geem Z W,Kim J H,Loganathan G V.A new heuristic optimiza-tion algorithm:harmony search[J].Simulation,2001,76(2):60-68
[8] Omran M G H,Mahdavi M.Global-best Harmony Search[J].A-pplied Mathematics and Computation,2008,198(2):643-656
[9] 周江嫚,黄清秀,彭敏放,等.基于差分进化优化ELM的模拟电路故障诊断[Z].计算机工程与应用,2012
[10] Honeynet Project.Know Your Enemy:Statistics[EB/OL].http://old.honeynet.org/papers/stats/,2001
[11] 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

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!