基于随机博弈的机会网络隐私保护机制

doi:10.3969/j.issn.1006-2475.2016.09.007

计算机与现代化 ›› 2016, Vol. 0 ›› Issue (9): 30-34.doi: 10.3969/j.issn.1006-2475.2016.09.007

基于随机博弈的机会网络隐私保护机制

(陕西工业职业技术学院，陕西咸阳712000)

收稿日期:2016-04-25 出版日期:2016-09-12 发布日期:2016-09-13
作者简介:何玉辉（1962-），男，陕西三原人，陕西工业职业技术学院副教授，硕士，研究方向：数据处理，图像处理和网络安全。

Privacy Preservation Mechanismin of Opportunistic Networks Based on Stochastic Game

(Shaanxi Polytechnic Institute, Xianyang 712000, China)

Received:2016-04-25 Online:2016-09-12 Published:2016-09-13

摘要/Abstract

摘要： 机会网络在数据转发过程中，由于需要依靠陌生节点帮助转发信息或者接收来自陌生节点的数据，这种数据转发机制对普通用户来说具有严重的隐私安全隐患。因此，本文针对机会网络中存在恶意节点窃取用户隐私等安全问题，为机会网络中的用户设计出一种最佳防御策略来防止个人隐私泄露。首先，建立机会网络下的系统模型，使用马尔科夫链刻画普通用户的个人信息的变化过程。在系统模型的基础上，采用随机博弈理论对用户与攻击者之间的攻防关系进行建模；然后，提出一种基于极小极大学习算法的防御策略；最后，通过与传统防御算法的对比实验，证明该算法不但具有较快的收敛速度，且在满足一定用户服务质量的前提下，性能始终优于其他防御策略，是机会网络下一种高效的隐私保护安全机制。

关键词: 机会网络, 随机博弈；隐私保护机制；学习算法

Abstract: There exist severe privacy security risks on opportunistic networks because of the need to rely on unknown nodes to forward the message or receive data from strange nodes. Accordingly, an optimal defense strategy is designed to avoid privacy leaking in terms of privacy security problems which may be caused by attacks from malicious nodes on opportunistic networks. Firstly, we model an opportunistic network that depicts the changing process of user’s context using Markov chain. Based on the system model, we formulate the attack-defense relationship between users and attackers with the stochastic game. Then, we propose a defense strategy depending on the min-max learning algorithm. At last, we prove the efficiency of this algorithm to protect privacy security by comparing with other traditional defense algorithms, which not only prove the higher convergence speed of the proposed algorithm, but also outperform better than others with user’s QoS guaranteed.

Key words: opportunistic networks, stochastic game, privacy preservation mechanism, learning algorithm

中图分类号:

TP393

何玉辉. 基于随机博弈的机会网络隐私保护机制[J]. 计算机与现代化, 2016, 0(9): 30-34.

HE Yu-hui. Privacy Preservation Mechanismin of Opportunistic Networks Based on Stochastic Game[J]. Computer and Modernization, 2016, 0(9): 30-34.

参考文献

［1］ Conti M, Giordano S. Mobile ad hoc networking: Milestones, challenges, and new research directions［J］. IEEE Communications Magazine, 2014,52(1):85-96.
［2］马华东,袁培燕,赵东. 移动机会网络路由问题研究进展［J］. 软件学报, 2015,26(3):600-616.
［3］ Zhu Ying, Xu Bin, Shi Xinghua, et al. A survey of socialbased routing in delay tolerant networks: Positive and negative social effects［J］. IEEE Communications Surveys & Tutorials, 2013,15(1):387-401.
［4］ Sweeney L. Kanonymity: A model for protecting privacy［J］. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2002,10(5):557-570.
［5］ Radenkovic M, Vaghi I. Adaptive user anonymity for mobile opportunistic networks［C］// Proceedings of the 7th ACM International Workshop on Challenged Networks. 2012:79-82.
［6］ Radenkovic M, Benslimane A, McAuley D. Reputation aware obfuscation for mobile opportunistic networks［J］. IEEE Transactions on Parallel and Distributed Systems, 2015,26(1):230-240.
［7］ Li Na, Das S K. A trustbased framework for data forwarding in opportunistic networks［J］. Ad Hoc Networks, 2013,11(4):1497-1509.
［8］〖JP2〗Gupta S, Dhurandher S K, Woungang I, et al. Trust-based security protocol against blackhole attacks in opportunistic networks［C］// 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). 2013:724-729.
［9］施仁杰. 马尔科夫链基础及其应用［M］. 西安：西安电子科技大学出版社, 1992.
［10］付钰,陈永强,吴晓平,等. 基于随机博弈模型的网络攻防策略选取［J］. 北京邮电大学学报, 2014,37(s1):35-39.
［11］Lee G, Kim H, Cho Y, et al. QoEaware scheduling for Sigmoid optimization in wireless networks［J］. IEEE Communications Letters, 2014,18(11):1995-1998.
［12］Liu Li, Mao Shisong. The risk model of the expected discounted penalty function with constant interest force［J］. Acta Mathematica Scientia, 2006,26(3):509-518.
［13］Hamadène S, Mu R. Existence of Nash equilibrium points for Markovian non-zero-sum stochastic differential games with unbounded coefficients［J］. Stochastics An International Journal of Probability and Stochastic Processes, 2013,87(1):85-111.
［14］周华,周海军,马建锋. 基于博弈论的入侵容忍系统安全性分析模型［J］. 电子与信息学报, 2013,35(8):19331939.
［15］刘陶,何炎祥,熊琦. 一种基于Q学习的LDoS攻击实时防御机制及其CPN实现［J］. 计算机研究与发展, 2015,48(3):432-439.
［16］Eagle N, Pentland A. Reality mining: Sensing complex social systems［J］. Personal and Ubiquitous Computing, 2006,10(4):255-268.
［17］Wang Chun, Dargahi F, Bhuiyan M F H. On the tradeoff between privacy and efficiency: A bidding mechanism for scheduling noncommercial services［J］. Computers in Industry, 2012,63(6):610-618.
［18］Lu Rongxing, Li Xiaodong, Luan T H, et al. Pseudonym changing at social spots: An effective strategy for location privacy in vanets［J］. IEEE Transactions on Vehicular Technology, 2012,61(1):86-96.

[1]	刘喜勋. 基于社会自私性的机会网络路由算法[J]. 计算机与现代化, 2016, 0(8): 91-96.
[2]	戚娜. 基于机会网络的资源共享路由策略研究与仿真[J]. 计算机与现代化, 2015, 0(9): 72-76.

基于随机博弈的机会网络隐私保护机制

Privacy Preservation Mechanismin of Opportunistic Networks Based on Stochastic Game

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 2

编辑推荐

Metrics

本文评价