Abstract
This paper proposed an anti-collusion trust model in order to resist collusion attack which has become the first threat in trust models of P2P networks. This trust model could detect the existing colluding peers and give them a penalty by introducing two penalty factors. When we evaluate the global trust value of a peer in the network, we consider not only the local trust values but also the recommended trust value of this peer. The convergence of iteration of global trust value is also taken into consideration and proved as well. Experiment results show that our anti-collusion trust model is effective in resisting collusion and also increasing the fraction of authentic downloads.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zhou, R., Hwang, K.: PowerTrust: A robust and scalable reputation system for trusted peer-to-peer computing. IEEE Trans. Parall. Distr. 18(4), 460–473 (2007)
Zhou, R., Hwang, K., Cai, M.: GossipTrust for fast reputation aggregation in peer-to-peer networks. IEEE Trans. Knowl. Data En. 20(9), 1282–1295 (2008)
Hughes, D., Coulson, G., Walkerdine, J.: Free riding on Gnutella revisited: The Bell tolls? IEEE Distributed Systems Onlin. 6(6), 1–18 (2005)
Sit, E., Morris, R.: Security considerations for P2P distributed hash tables. In: Druschel, P., Kaashoek, M.F., Rowstron, A. (eds.) IPTPS 2002. LNCS, vol. 2429, pp. 261–266. Springer, Heidelberg (2002)
Kamvar, S.D., Schlosser, M.T., Molina, H.G.: The eigentrust algorithm for reputation management in P2P networks. In: Proceedings of the 12th International World Wide Web Conference (WWW 2003), pp. 640–651. ACM, New York (2003)
Xiong, L., Liu, L.: PeerTrust: Supporting reputation-based trust for peer-to-peer electronic communities. IEEE Trans. Knowl. Data En. 16(7), 843–857 (2004)
Chen, K., Hwang, K., Chen, G.: Heuristic discovery of role-based trust chains in peer-to-peer networks. IEEE Trans. Parall. Distr. 20(1), 83–96 (2009)
Hoffman, K., Zage, D., Nita-Rotaru, C.: A survey of attack and defense techniques for reputation systems. ACM Comput. Surv. 5(9), 1–34 (2007)
Miao, G., Feng, D., Su, P.: Colluding clique detector based on activity similarity in P2P trust model. Journal on Communications 30(8), 9–20 (2009) (in Chinese)
Dou, W., Wang, H., Jia, Y., Zou, P.: A recommendation-based peer-to-peer trust model. Journal of Software 15(4), 571–583 (2004) (in Chinese)
Yu, H., Gibbons, P.B., Kaminsky, M., Xiao, F.: SybilLimit: A near-optimal social network defense against sybil attacks. IEEE Trans. Network 18(3), 885–898 (2010)
Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International World Wide Web Conference (WWW 2001), pp. 285–295. ACM, New York (2001)
Ou-Yang, J., Lin, Y., Zhou, S., Tan, Y.: A global trust model to suppress the oscillating behavior of peers for P2P environments. Journal of Hunan University (Natural Science) 35(8), 68–72 (2008) (in Chinese)
Stoica, I., Morris, R., Karger, D., Kaashoek, M.F., Balakrishnan, H.: Chord: A scalable peer-to-peer lookup service for Internet applications. In: Proceedings of the 2001 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM 2001), vol. 31, pp. 149–160. ACM, New York (2001)
Li, J., Jing, Y., Xiao, X., Wang, X., Zhang, G.: A trust model based on similarity-weighted recommendation for P2P environments. Journal of Software 18(1), 157–167 (2007) (in Chinese)
Stanford P2P Sociology Project, http://p2p.stanford.edu/www/projects.htm
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tang, X., Wang, R., Huang, H. (2011). An Anti-collusion Trust Model in P2P Networks. In: Gong, Z., Luo, X., Chen, J., Lei, J., Wang, F.L. (eds) Web Information Systems and Mining. WISM 2011. Lecture Notes in Computer Science, vol 6987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23971-7_43
Download citation
DOI: https://doi.org/10.1007/978-3-642-23971-7_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23970-0
Online ISBN: 978-3-642-23971-7
eBook Packages: Computer ScienceComputer Science (R0)