基于灰色理论的P2P网络行为分析与预测
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摘要
目前P2P网络的应用越来越广泛,P2P技术已经应用很多的领域。P2P网络具有动态性、可扩展性、自组织、非中心化的特点,使得P2P网络存在很大的安全隐患,使得节点之间缺乏信任,很大程度上限制了P2P网络的进一步发展,因此能否有效可靠的对节点进行行为分析与预测是保障高质量资源共享的重要因素。
针对P2P网络特点,在深入研究灰色理论的基础上,将灰色关联投影、灰预测相结合,阐述了基于投影的灰色行为分析模型(GBAP),对对等网络(P2P)中的节点进行行为分析与预测。主要分成两个部分,包括节点的行为分析和节点的行为预测。节点的行为分析主要是将多目标决策的灰色关联投影用于节点的鉴别,计算各个节点关于理想节点的映射值,以此来作为节点性能评判的指标。节点的行为预测主要是对每个节点的映射值进行灰生成,达到极性统一的效果,然后建立灰模型,这里采用平滑型GM(1,1)模型,之后进行灰预测,以此作为节点未来行为预测的指标,最后计算节点的滚动残差,得到节点的可信度,对灰预测模型的性能进行阐述。
在采集P2P网络数据的基础上,计算了四个节点相对于理想节点的映射值,并对上述数据进行了主成分分析,将映射值和主成分分析结果进行了对比,同时对节点进行了预测,对四个节点的各方面性能进行了详细分析与比较,结果表明,基于投影的灰色行为分析模型是对P2P网络中节点行为分析与预测的有效方法,该方法对提高P2P网络评价的客观性有着积极的意义,对P2P网络的安全通信奠定了良好的基础。
Currently P2P networks used more wide, and P2P technology has been applied in a lot of fields. P2P network is dynamic, expansible, self-organization and non-centralized, which result in a big security problem in the P2P network and the lack of trust between nodes, so that largely impede the further development of P2P networks. Therefore nodes behavior analysis and prediction is an important factor in the sharing of resources.
For the features of P2P networks and on the basis of deep study of grey theory, we correlate grey relation projection to grey prediction and propose grey behavior analysis based on projection method or GBAP in short, for the behavior analysis and prediction of nodes in P2P networks. GBAP can be divided into two parts, including the node behavior analysis and the node behavior prediction. The work of node behavior analysis is to apply grey relation projection to the node identification, then calculate projection value of each candidate node to the ideal node, in order to evaluate the performance of node. The node behavior prediction is to apply grey generating on the projection value of each node, in order to unify the goal nature of series, and then generate grey module, here we use SmoGM(1,1) module, after that, we calculate the prediction value for the behavior prediction of node, at last calculate the residual error and get the credibility of the node, the analysis the performance of the grey prediction module.
On the base of collect all the data of P2P network, paper calculate projection value of the four candidate node to the ideal node, and apply principal component analysis on the same data, the compared the projection value and the result of principal component analysis, then carry detailed analysis and comparison on the all kinds aspects of four nodes performance. The result show that grey behavior analysis based on projection is an effective method for the nodes behavior analysis and prediction in P2P network, it helps improve the objectivity of P2P networks evaluation and lay a good foundation for secure communications in the P2P network.
针对P2P网络特点,在深入研究灰色理论的基础上,将灰色关联投影、灰预测相结合,阐述了基于投影的灰色行为分析模型(GBAP),对对等网络(P2P)中的节点进行行为分析与预测。主要分成两个部分,包括节点的行为分析和节点的行为预测。节点的行为分析主要是将多目标决策的灰色关联投影用于节点的鉴别,计算各个节点关于理想节点的映射值,以此来作为节点性能评判的指标。节点的行为预测主要是对每个节点的映射值进行灰生成,达到极性统一的效果,然后建立灰模型,这里采用平滑型GM(1,1)模型,之后进行灰预测,以此作为节点未来行为预测的指标,最后计算节点的滚动残差,得到节点的可信度,对灰预测模型的性能进行阐述。
在采集P2P网络数据的基础上,计算了四个节点相对于理想节点的映射值,并对上述数据进行了主成分分析,将映射值和主成分分析结果进行了对比,同时对节点进行了预测,对四个节点的各方面性能进行了详细分析与比较,结果表明,基于投影的灰色行为分析模型是对P2P网络中节点行为分析与预测的有效方法,该方法对提高P2P网络评价的客观性有着积极的意义,对P2P网络的安全通信奠定了良好的基础。
Currently P2P networks used more wide, and P2P technology has been applied in a lot of fields. P2P network is dynamic, expansible, self-organization and non-centralized, which result in a big security problem in the P2P network and the lack of trust between nodes, so that largely impede the further development of P2P networks. Therefore nodes behavior analysis and prediction is an important factor in the sharing of resources.
For the features of P2P networks and on the basis of deep study of grey theory, we correlate grey relation projection to grey prediction and propose grey behavior analysis based on projection method or GBAP in short, for the behavior analysis and prediction of nodes in P2P networks. GBAP can be divided into two parts, including the node behavior analysis and the node behavior prediction. The work of node behavior analysis is to apply grey relation projection to the node identification, then calculate projection value of each candidate node to the ideal node, in order to evaluate the performance of node. The node behavior prediction is to apply grey generating on the projection value of each node, in order to unify the goal nature of series, and then generate grey module, here we use SmoGM(1,1) module, after that, we calculate the prediction value for the behavior prediction of node, at last calculate the residual error and get the credibility of the node, the analysis the performance of the grey prediction module.
On the base of collect all the data of P2P network, paper calculate projection value of the four candidate node to the ideal node, and apply principal component analysis on the same data, the compared the projection value and the result of principal component analysis, then carry detailed analysis and comparison on the all kinds aspects of four nodes performance. The result show that grey behavior analysis based on projection is an effective method for the nodes behavior analysis and prediction in P2P network, it helps improve the objectivity of P2P networks evaluation and lay a good foundation for secure communications in the P2P network.
引文
[1]李之棠,祝幼菁,王阜东.一种完全匿名的P2P网络信任模型.计算机工程与科学. 2006, 28(11): 9~11
[2]刘宝旭,李雪莹,于传松,许榕生.对等网技术及应用概述.计算机工程与应用. 2003, 18: 1~3
[3]常璐璐,禹继国.基于P2P网络安全问题的研究.网络通讯及安全. 2008: 819~820
[4]贺秦禄.基于P2P网络安全信任机制的研究.西安建筑科技大学硕士学位论文, 2008
[5] Beth T, Borcherding M, Klein B. Valuation of trust in open network. In Proceedings of the European Symposium on Research in Security[C]. Brighton: Springer-Verlag, 1994,3~18
[6]徐锋,吕建. Web安全中的信任管理研究与进展.软件学报, 2002, 13(11): 2057~2064
[7] Wang Y, Vassileva J. Bayesian network trust model in peer to peer networks. Proceedings of t he 2nd International Workshop: AP2PC 2003—Agent s and Peer to Peer Computing. Melbourne , Aust ralia: Springer Verlag, Heidelberg, D269121, Germany, 2003 : 23~24
[8] Zhiwei Qin, Zhiping Jia, Xihui Chen. Fuzzy Dynamic Programming based Trusted Routing Decision in Mobile Ad Hoc Networks. Embedded Computing, 2008. SEC 08. Fifth IEEE International Symposium. Beijing, China, IEEE Press: 180~185
[9] Tang W, Chen Z. Research of subjective trust management model based on the fuzzy set theory. Chinese Journal of Software,2003, 14 (8) : 1401~1408
[10] Hallani H., Shahrestani S.A. Trust assessmentt in wireless Ad-hoc networks. 2008 1st IFIP Wireless Days, WD 2008
[11] Yu B, Munindar P. An evidential of distributed reputation management. Proceedings of t he 1st International Joint Conference on: Autonomous Agents and Multiagent Systems (AAMAS02). Bologna, Italy: ACM Press, 2002: 294~301
[12] J?sang A. Trust based decision making for electronic transactions. Yngstrom L, Svensson T eds. Proceedings of the 4th Nordic Workshop on Secure Computer Systems. Kista: Stockholm University Press, 1999: 1~21
[13] Abdul Rahman A, Hailes S. A distributed trust model. Proceedings of t he 1997 New Security Paradigms Workshop. Cumbria, U K: ACM Press, 1998: 48~60
[14] Theodorakopoulos G, Baras J S. Trust evaluation in Ad Hoc networks. Proceedings of t he 2004 ACM Workshop on Wireless Security. Philadelphia, USA: ACM Press , 2004 : 1~10
[15] Buchegger S, Boudec J L. A robust reputation system for P2P and mobile Ad Hoc networks. Proceedings of the 2nd Workshop on the Economics of Peer to Peer Systems. Harvard University, Boston, Cambridge MA, 2004: 1~10
[16] Xiong L, Liu L. Peer Trust: Supporting reputation based trust in peer to peer communities. IEEE Transactions on Data and Knowledge Engineering, Special Issue on Peer to Peer Based Data Management, 2004, 16 (7): 843~857
[17] YaoWang, Julita Vassileva.Trust and reputation model in peer-to-peer networks. Proceedings of the Third International Conference on Peer-to-Peer Computing, 2003 IEEE: 150~157
[18] K.Aberer, Z.Despotovic. Managing Trust in a Peer-To-Peer Information System. Proceedings of ACM International Conference on Information and Knowledge Management (CIKM), 2001: 422~431
[19] S.Kamvar, M.Schlosser, H.Garcia-Molina. The Eigentrust Algorithm for Reputation Management in P2P Networks.In:Proceedings.of the Twelfth International World Wide Web Conference.Budapest:ACM Press, 2003: 640~651
[20] Fu Cai,Hong Fan,et al. Self-Organized Public-Key Management for Mobile Ad Hoc Networks based on a Bidirectional Trust Model.Wuhan University Journal of Natural Science, 2006,1,11(1): 1188~1189
[21] Fan Hong, Cai Fu, Liang Hong, Jing Chen. Bridge Nodes Based Secure OLSR.2005 International Conference on Wireless Communications, Networking and mobile Computing.Wu Han, China: IEEE Press, 2005. 710~713
[22] Marti S, Giuli T J, Lai K, Baker M. Mitigating routing misbehavior in mobile Ad Hoc networks. Proceedings of the 6th ACM International Conference on Mobile Computing and Networking. NY USA, ACM, 2000: 255-265Gadi Evron, David Maynor, Noam Rathaus etc. Open Source Fuzzing Tools. Syngress Publishing, 2007
[23] Buchegger S, Boudec J L. Performance analysis of the CONFIDANT protocol: Cooperation of nodes fairness in dynamic Ad Hoc networks. Proceedings of the IEEE ACM Symposium on Mobile Ad Hoc Networking and Computing. Lausanne, 2002: 226~236
[24] Pietro Michiardi, Refik Molva. CORE: A collaborative reputation mechanism to enforce node cooperation in mobile Ad Hoc networks Proceedings of the 6th IFIP Conference on Security Communications and Multimedia (CMS 2002). Portoroz, Slovenia, 2002: 107~121
[25]姜涛,董照飞. P2P系统特点及安全性分析.沿海企业与科技, 2006, 78: 42~43
[26]张连峰,刘乃安,钱秀槟等.综述:对等网(P2P)技术.计算机工程与应用, 2003, 12: 142~145
[27]林怀青,李之棠. P2P信任模型关键技术的研究进展.小型微型计算机系统. 2007, 28(9): 1599~1603
[28] Deng Julong. Undulating grey model (UGM) GM(1, 1|tan(k-τ)p,sin(k-τ)p). The Journal of Grey System, 2001, 13(3): 201~205
[29]邓聚龙.灰色系统基本方法.武汉:华中科技大学出版社, 2005: 2~4
[30] Fu Cai, Hong Fan, Hong Liang, Peng Bing, Cui YongQuan. Mobile Ad Hoc Secure Routing Protocol based on Trust Preserving. Chinese Journal of Computer.2007.10(30): 1853~1863
[31] Xu LanFang, Hu HuaiFei, Sang ZiXia, Xu Fengming, Zou Deqing. A Prestige Reporting Mechanism Based on Gray System Theory. Chinese Journal of Software. 2007, 18(7): 1730~1737
[32]谢科范.评灰色系统理论.系统工程. 1991, 9(4): 49~52
[33]水乃翔,董太亨.关于灰关联度的一些理论问题.系统工程. 1992, 10(6). 23~26
[34]唐五湘.灰色绝对关联度的缺陷.系统工程. 1994, 12(5). 59~62
[35]朱宝璋.关于灰色系统基本方法的研究与评论.系统工程理论与实践. 1994, 14(4): 19~23
[36]夏军,王中根.生态环境质量评价指标体系及多级灰关联评价方法[J].生态学研究, 1998, 4(2): 8~11
[37]邓聚龙.灰色预测与决策.武汉:华中科技大学出版社, 2002
[38]吕锋,崔晓辉.多目标决策灰色关联投影法及其应用.系统工程理论与实践: 2005: 103~107
[39]门宝辉,赵燮京,梁川.多目标决策灰色关联投影法在水利工程开发中的应用.武汉大学学报. 2003, 36(4): 36~39
[40]袁晓宇.多目标决策灰色关联投影法在水资源承载恩能够力分析中的应用.江苏水利. 2004, 12: 10~13
[41]李华斌,严力蛟,赵晓慧.利用灰色关联投影模型进行生态适宜度评价.科技通报, 2008, 24(5): 714~720
[42]赵晓慧,严力蛟.生态敏感性的灰色关联投影评价模型及其应用.浙江大学学报. 2006, 32(3): 341~345
[43] George H. Dunteman, Principal Component Analysis, United States of America: Sage Publications, 1989
[2]刘宝旭,李雪莹,于传松,许榕生.对等网技术及应用概述.计算机工程与应用. 2003, 18: 1~3
[3]常璐璐,禹继国.基于P2P网络安全问题的研究.网络通讯及安全. 2008: 819~820
[4]贺秦禄.基于P2P网络安全信任机制的研究.西安建筑科技大学硕士学位论文, 2008
[5] Beth T, Borcherding M, Klein B. Valuation of trust in open network. In Proceedings of the European Symposium on Research in Security[C]. Brighton: Springer-Verlag, 1994,3~18
[6]徐锋,吕建. Web安全中的信任管理研究与进展.软件学报, 2002, 13(11): 2057~2064
[7] Wang Y, Vassileva J. Bayesian network trust model in peer to peer networks. Proceedings of t he 2nd International Workshop: AP2PC 2003—Agent s and Peer to Peer Computing. Melbourne , Aust ralia: Springer Verlag, Heidelberg, D269121, Germany, 2003 : 23~24
[8] Zhiwei Qin, Zhiping Jia, Xihui Chen. Fuzzy Dynamic Programming based Trusted Routing Decision in Mobile Ad Hoc Networks. Embedded Computing, 2008. SEC 08. Fifth IEEE International Symposium. Beijing, China, IEEE Press: 180~185
[9] Tang W, Chen Z. Research of subjective trust management model based on the fuzzy set theory. Chinese Journal of Software,2003, 14 (8) : 1401~1408
[10] Hallani H., Shahrestani S.A. Trust assessmentt in wireless Ad-hoc networks. 2008 1st IFIP Wireless Days, WD 2008
[11] Yu B, Munindar P. An evidential of distributed reputation management. Proceedings of t he 1st International Joint Conference on: Autonomous Agents and Multiagent Systems (AAMAS02). Bologna, Italy: ACM Press, 2002: 294~301
[12] J?sang A. Trust based decision making for electronic transactions. Yngstrom L, Svensson T eds. Proceedings of the 4th Nordic Workshop on Secure Computer Systems. Kista: Stockholm University Press, 1999: 1~21
[13] Abdul Rahman A, Hailes S. A distributed trust model. Proceedings of t he 1997 New Security Paradigms Workshop. Cumbria, U K: ACM Press, 1998: 48~60
[14] Theodorakopoulos G, Baras J S. Trust evaluation in Ad Hoc networks. Proceedings of t he 2004 ACM Workshop on Wireless Security. Philadelphia, USA: ACM Press , 2004 : 1~10
[15] Buchegger S, Boudec J L. A robust reputation system for P2P and mobile Ad Hoc networks. Proceedings of the 2nd Workshop on the Economics of Peer to Peer Systems. Harvard University, Boston, Cambridge MA, 2004: 1~10
[16] Xiong L, Liu L. Peer Trust: Supporting reputation based trust in peer to peer communities. IEEE Transactions on Data and Knowledge Engineering, Special Issue on Peer to Peer Based Data Management, 2004, 16 (7): 843~857
[17] YaoWang, Julita Vassileva.Trust and reputation model in peer-to-peer networks. Proceedings of the Third International Conference on Peer-to-Peer Computing, 2003 IEEE: 150~157
[18] K.Aberer, Z.Despotovic. Managing Trust in a Peer-To-Peer Information System. Proceedings of ACM International Conference on Information and Knowledge Management (CIKM), 2001: 422~431
[19] S.Kamvar, M.Schlosser, H.Garcia-Molina. The Eigentrust Algorithm for Reputation Management in P2P Networks.In:Proceedings.of the Twelfth International World Wide Web Conference.Budapest:ACM Press, 2003: 640~651
[20] Fu Cai,Hong Fan,et al. Self-Organized Public-Key Management for Mobile Ad Hoc Networks based on a Bidirectional Trust Model.Wuhan University Journal of Natural Science, 2006,1,11(1): 1188~1189
[21] Fan Hong, Cai Fu, Liang Hong, Jing Chen. Bridge Nodes Based Secure OLSR.2005 International Conference on Wireless Communications, Networking and mobile Computing.Wu Han, China: IEEE Press, 2005. 710~713
[22] Marti S, Giuli T J, Lai K, Baker M. Mitigating routing misbehavior in mobile Ad Hoc networks. Proceedings of the 6th ACM International Conference on Mobile Computing and Networking. NY USA, ACM, 2000: 255-265Gadi Evron, David Maynor, Noam Rathaus etc. Open Source Fuzzing Tools. Syngress Publishing, 2007
[23] Buchegger S, Boudec J L. Performance analysis of the CONFIDANT protocol: Cooperation of nodes fairness in dynamic Ad Hoc networks. Proceedings of the IEEE ACM Symposium on Mobile Ad Hoc Networking and Computing. Lausanne, 2002: 226~236
[24] Pietro Michiardi, Refik Molva. CORE: A collaborative reputation mechanism to enforce node cooperation in mobile Ad Hoc networks Proceedings of the 6th IFIP Conference on Security Communications and Multimedia (CMS 2002). Portoroz, Slovenia, 2002: 107~121
[25]姜涛,董照飞. P2P系统特点及安全性分析.沿海企业与科技, 2006, 78: 42~43
[26]张连峰,刘乃安,钱秀槟等.综述:对等网(P2P)技术.计算机工程与应用, 2003, 12: 142~145
[27]林怀青,李之棠. P2P信任模型关键技术的研究进展.小型微型计算机系统. 2007, 28(9): 1599~1603
[28] Deng Julong. Undulating grey model (UGM) GM(1, 1|tan(k-τ)p,sin(k-τ)p). The Journal of Grey System, 2001, 13(3): 201~205
[29]邓聚龙.灰色系统基本方法.武汉:华中科技大学出版社, 2005: 2~4
[30] Fu Cai, Hong Fan, Hong Liang, Peng Bing, Cui YongQuan. Mobile Ad Hoc Secure Routing Protocol based on Trust Preserving. Chinese Journal of Computer.2007.10(30): 1853~1863
[31] Xu LanFang, Hu HuaiFei, Sang ZiXia, Xu Fengming, Zou Deqing. A Prestige Reporting Mechanism Based on Gray System Theory. Chinese Journal of Software. 2007, 18(7): 1730~1737
[32]谢科范.评灰色系统理论.系统工程. 1991, 9(4): 49~52
[33]水乃翔,董太亨.关于灰关联度的一些理论问题.系统工程. 1992, 10(6). 23~26
[34]唐五湘.灰色绝对关联度的缺陷.系统工程. 1994, 12(5). 59~62
[35]朱宝璋.关于灰色系统基本方法的研究与评论.系统工程理论与实践. 1994, 14(4): 19~23
[36]夏军,王中根.生态环境质量评价指标体系及多级灰关联评价方法[J].生态学研究, 1998, 4(2): 8~11
[37]邓聚龙.灰色预测与决策.武汉:华中科技大学出版社, 2002
[38]吕锋,崔晓辉.多目标决策灰色关联投影法及其应用.系统工程理论与实践: 2005: 103~107
[39]门宝辉,赵燮京,梁川.多目标决策灰色关联投影法在水利工程开发中的应用.武汉大学学报. 2003, 36(4): 36~39
[40]袁晓宇.多目标决策灰色关联投影法在水资源承载恩能够力分析中的应用.江苏水利. 2004, 12: 10~13
[41]李华斌,严力蛟,赵晓慧.利用灰色关联投影模型进行生态适宜度评价.科技通报, 2008, 24(5): 714~720
[42]赵晓慧,严力蛟.生态敏感性的灰色关联投影评价模型及其应用.浙江大学学报. 2006, 32(3): 341~345
[43] George H. Dunteman, Principal Component Analysis, United States of America: Sage Publications, 1989