电信科学 ›› 2018, Vol. 34 ›› Issue (9): 78-86.doi: 10.11959/j.issn.1000-0801.2018259

• 研究与开发 • 上一篇    下一篇

基于云计算和动态贝叶斯博弈的WSN恶意程序传播优化抑制方法

沈士根1,冯晟1,周海平1,黄龙军1,胡珂立1,曹奇英2   

  1. 1 绍兴文理学院计算机科学与工程系,浙江 绍兴 312000
    2 东华大学计算机科学与技术学院,上海 201620
  • 出版日期:2018-09-20 发布日期:2018-10-12
  • 基金资助:
    国家自然科学基金资助项目

Optimal approach of suppressing WSN malware propagation based on cloud computing and dynamic Bayesian game

Shigen SHEN1,Sheng FENG1,Haiping ZHOU1,Longjun HUANG1,Keli HU1,Qiying CAO2   

  1. 1 Department of Computer Science and Engineering,Shaoxing University,Shaoxing 312000,China
    2 College of Computer Science and Technology,Donghua University,Shanghai 201620,China
  • Online:2018-09-20 Published:2018-10-12
  • Supported by:
    The National Natural Science Foundation of China

摘要:

为有效地应用入侵检测系统检测WSN(wireless sensor network,无线传感网络)恶意程序从而抑制WSN恶意程序传播,在考虑WSN节点资源有限和云计算平台资源几乎无限的现状基础上,借助云计算平台提出WSN入侵检测网络结构。依据传感节点和WSN入侵检测代理之间博弈过程的分析,使用动态贝叶斯博弈建立了考虑WSN入侵检测代理监控数据发送能耗和传感节点隐私保护需求的WSN恶意程序传播抑制博弈模型。依据建立的博弈类型,并基于精炼贝叶斯均衡提出抑制WSN恶意程序传播的优化策略,并给出具体的算法。实验分析了影响WSN入侵检测代理选择优化策略的因素,为具体应用提供了实验依据。

关键词: WSN, 恶意程序, 入侵检测系统, 云计算, 动态贝叶斯博弈

Abstract:

To apply intrusion detection system (IDS) efficiently so as to suppress WSN malware propagation,a cloud-based network infrastructure for realizing functions of WSN IDS was presented,considering the real basis that the resources of WSN nodes were limited whilst the resources of cloud computing platform were almost unlimited.Based on the analysis of the game process between a sensor node and the corresponding WSN IDS agent,a WSN-malware-propagation-suppression game model was constructed by employing the dynamic Bayesian game,and the requirements of energy consumption in sending monitored data and privacy protection for sensor nodes were satisfied.According to the proposed game type and refined Bayesian equilibrium,the optimal strategie for suppressing WSN malware was proposed as well the algorithm for actual application was given.The factors that influence WSN IDS agents to select their optimal strategies were analyzed,and the experimental foundation was provided for the application of the proposed approach.

Key words: wireless sensor network, malware, intrusion detection system, cloud computing, dynamic Bayesian game

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