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The Research Based on Trust Value against Vulnerability in P2P Networks

The Research Based on Trust Value against Vulnerability in P2P Networks. Yuhua Liu, Yuling Li, Wei Chen, Kaihua Xu. Department of Computer Science Huazhong Normal University Wuhan, China Email:yhliu@mail.ccnu.edu.cn. Outline. Introduction Background of Research

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The Research Based on Trust Value against Vulnerability in P2P Networks

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  1. The Research Based on Trust Value against Vulnerability in P2P Networks Yuhua Liu, Yuling Li, Wei Chen, Kaihua Xu Department of Computer Science Huazhong Normal University Wuhan, China Email:yhliu@mail.ccnu.edu.cn

  2. Outline • Introduction • Background of Research • The Model Based on Trust Value Against Vulnerability in P2P Network • The Ideology of AgainstVulnerability Model • Node’s Trust Value for Type of Resources • The Calculation of trust value • Selected Resources Provider Nodes • The Analysis of Vulnerability Against Model • Simulation Experiment • Select Parameters’ value • The Node’s Connections and Success Rate of Transactions in P2P Network • Conclusions

  3. Introduction • P2P network breaks the traditional C/S mode, in this network, each node is equal logically, which is both a provider and recipient of resources. P2P file sharing business has exceeded the WWW, and becomes one of the most important internet application systems in the world. • There exist a small number of nodes that have a large number of connections in P2P network, and these nodes is what we called hubs. The existence of the hubs causes the entire network’s ability of defending against coordinated attacks to decrease greatly, and increase the vulnerability of the network .

  4. Research Background(1/2) • At present, the controlling mechanisms on hubs mainly focus on the aspect of restricting the behavior of the users for the single node, such as incentive mechanisms, the game theory, social networks or economic models and other methods of controlling strategy. • Such methods may make the system no longer attractive to some of the free-riders and reduce the number of its users.

  5. Research Background(2/2) • In addition, another noteworthy research perspective in P2P network is to control the network’s logical topology structure to avoid generating the hubs. • It just consider the remainder connections of node and the distance between nodes, without concerning the node's trust value.

  6. The Ideology of AgainstVulnerability Model • Definition 1: P2P network will be expressed as G (V, E), in which V is the nodes set and E is the edges set, (i, j=1, 2… n) ，n is the number of nodes, and the number of the edges connected to the node is called node’s connections. • When vi sent the transaction request to vj, select the node who have higher value and fewer connections preferentially.

  7. Node’s Trust Value for Type of Resources • Trust can be used to portray the relationship between nodes. • The trust value in this article is that vi gets the degree of vj in accordance with its historical experience and other nodes’ recommend. which is decided by the degree of satisfaction with transactions between nodes in the trust model of P2P networks.

  8. The Calculation of trust value (1) • Definition 2: Dij (k) denotes the direct trust value merchandising between vi and vj for the k type resource, which is calculated through the direct historical transactions between vi and vj, such as (1) follows: • sij(k) means the number of successes of merchandising between vi and vj for k type resource; • fij(k) express the number of failures; • ρ is on behalf of the trust value of attenuation factor, and used to adjust the decreasing speed rate of direct trust value because of failure transactions; • λ restricts the speed of node from the first trust to complete trust;

  9. The Calculation of trust value (2) • Definition 3: Rtj(k) dotes the recommend trust value of vj about k type resources (from the perspective of vi), which depends on the node's own general value (definition 3) and the direct trust value between commend nodes and vj, such as (2) below: • Bj(k) expresses the set of nods who have transact with vj except vi about k type resource, Dxj(k) expresses the direct trust value of vj from vx, Tx(k) expresses the general trust value of k type resource in set vx.

  10. The Calculation of trust value (3) • Definition 4: Tij(k) denotes the general trust value of vj from vi, that is the sum of direct trust value Dij(k) and recommend trust value Rij(k) , such as ( 3) follows: • α is factor of direct trust, while β is factor of recommend trust, and α+β=1, the value of α and β is decided by the calculation of general trust value mostly based on their own historical experience of the transactions, or the recommendation of other nodes.

  11. The Calculation of trust value (4) • Definition 5: Qij(k) denotes the ultimate reference value of selecting the resources provider, such as (4) follows: • N (i) is the greatest number of concurrent download connections of each node, and D (i) () is the connections of node.

  12. The Analysis of Vulnerability Against Model • The stability of network: The setting of λ makes the accumulation of trust value need a certain amount of time, so it can hold back whitewashing phenomenon to a certain extent and maintain stability of network. • Collusion and slander: By formula (3), integrate trust value is decided by direct trust value and recommend trust value. • Unreliable service and fraud behavior: This paper adopts method of calculating trust value of nodes for types of resources, if the transaction fails because of providing unreliable service or fraud behavior, the existence of factor ρ will make node pay more cost and the directly trust value Dij(k) will be reduced.

  13. Select Parameters’ value(1) • The analysis of parameter ρ Fig 1 shows the effect of the number of successful transactions sij(k) and failures transactions fij(k) to Dij(k) with λ = 5, and ρ in the case of 1, 5, 20 respectively. Fig 1. The impact of ρ to the direct trust value Dij(k)

  14. Select Parameters’ value(2) • The analysis of parameter λ Fig 2 shows the effect of the number of successes transactions sij(k) and failures transactions fij(k)to Dij(k) when ρ = 3, λ in the case of 1,10,100 respectively Fig 2. The impact of λ to the direct trust value Dij(k)

  15. Select Parameters’ value(3) • Analyze the value of parameters ρ and λ • With the greater value of ρ and λ, the quality of network’s service is required more strict, the better service users can receive. • The accumulation of trust value is too difficult, which will reduce the nodes’ enthusiasm to make transaction; On the contrary, a lower value of ρ and λ can’t reflect the punishment for the failure transactions • Through many experiments and analysis of actual data, this paper select ρ=2 and λ=10 according to the scale of network. However the value of ρ and λ can be adjusted properly.

  16. The Node’s Connections and Success Rate of Transactions in P2P Network(1) Fig 3. Compare node’s connections in two networks As we can see from Figure 4, the number of hubs reduce obviously in the controlling network based on the trust value of nodes than non-controlling network.

  17. The Node’s Connections and Success Rate of Transactions in P2P Network(2) Fig 4. Compare the success rate of transactions in two networks Seen from Figure 5, success rate of transactions in the controlling network based on the trust value of nodes is significantly higher than non-controlling network.

  18. Conclusions • This ensures the service provided by the node, and avoids the negative effects caused by the number of network users to decrease because of strict mechanism. • Simulation proves that this model not only can effectively avoid the formation of hubs, improve the ability of against coordinated attack in P2P network, enhance the network robustness and stability, also can significantly improve the success rate of the transactions and the efficiency of the network.

  19. Reference • Wang, Y, Vassileva J. Trust and reputation model in peer-to-peer networks. Peer-to-Peer Computing, 2003. (P2P 2003). [C]// Proceedings. Third International Conference on, 1-3 Sept. 2003, Pages: 150-157. • Huu Tran, Hitchens M, Varadharajan V, Watters P. A Trust based AccessControl Framework for P2P File-Sharing systems. System Sciences, 2005.HICSS '05 [C]//Proceedings of the 38th Annual Hawaii International Conference on, 03-06 Jan. 2005. Pages: 302c-302c. • Wenjie Wang, Hyunseok Chang, Amgad Zeitoun etal. "Characterizing Guarded Hosts in Peer-to-Peer File Sharing Systems", IEEE Global Communications Conference (Globecom 2004): 1539-1543. • Matei Ripeanu, Ian Foster and Adriana Iamnitchi. Mapping the Gnutella Network: Properties of Large-Scale Peer-to-Peer Systems and Implications for System Design. IEEE Internet Computing, vol. 6(1) 2002. • D. Hughes, G. Coulson, and J. Walkerdine. Free Riding on Gnutella. Revisited: The Bell Tolls? IEEE Distributed Systems Online, 6(6),. 2005. • Emmanuelle Anceaume, Maria Gradinariu, Aina Ravoaja. Incentive for P2P Fair Resource Sharing. Proceedings of the IEEE International Conference on Peer-to-Peer Computing (P2P’05): 253-260. • Gong Haigang, Liu Ming, Mao Yingchi et al. Research Advances in Key Technology of P2P-Based Media Streaming. Computer Research and Development, 2005, 42(12): 2033-2040.

  20. Rohit Gupta, Arun K. Somani. Game Theory As A Tool To Strategize As Well As Predict Nodes’ Behavior In Peer-to-Peer Networks. Proceedings of the 11th International Conference on Parallel and Distributed Systems (ICPADS'05): 244-249. • Xavier P, Wentong Cai, Bu-Sung Lee. Employing economics to achieve fairness in usage policing of cooperatively shared computing resources. Proceedings of 2005 IEEE International Symposium on Cluster Computing and the Grid(CCGrid 2005):326-333. • Yuhua Liu, Chun Yang, Kaihua Xu, Model of Controlling the Hubs in P2P Networks. Special Issue on the Recent Advances in Electronic Commerce and Security, Nanchang, China, 22-24, May 2009. • Oram A.Peer-to-Peer: Harnessing the Power of Disruptive Technology. Sebastopol: O’Reilly Press,2001.222-238. • Mauro Andreolini, Riccardo Lancellotti. Analysis of peer-to-peer systems: workload characterization and effects on traffic cacheability,.proceedings of the IEEE Computer Society’s 12th Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems(MASCOTS’04),2004. • Feldman I, Papadimit riou C, Chuang J, Stoica I. Free-riding and whitewashing in Peer-to-Peer systems. IEEE Journal of Selected Areas in Communications，2006, 24(5):1010-1019 • Dou W. The research on trust-aware P2P topologies and constructing technologies [Ph.D. Thesis]. Changsha: National University of Defense Technology, 2003 (in Chinese with English abstract)

  21. Thank you! 2009-8-8

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