Document Type : Methodologies


1 Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2 Department of Mathematics and Computer Sciences, Shahed University, Tehran, Iran.

3 Iran University of Medical Sciences, Tehran, Iran.



In cooperative P2P networks, there are two kinds of illegal users, namely free riders and Sybils. Free riders are those who try to receive services without any sort of cost. Sybil users are rational peers which have multiple fake identities. There are some techniques to detect free riders and Sybil users which have previously been proposed by a number of researchers such as the Tit-for-tat and Sybil guard techniques. Although such previously proposed techniques were quite successful in detecting free riders and Sybils individually, there is no technique capable of detecting both these riders simultaneously. Therefore, the main objective of this research is to propose a single mechanism to detect both kinds of these illegal users based on Game theory. Obtaining new centrality and bandwidth contribution formulas with an incentive mechanism approach is the basic idea of the present research’s proposed solution. The result of this paper shows that as the life of the network passes, free riders are identified, and through detecting Sybil nodes, the number of services offered to them will be decreased.


[1] Lua, E. K., Crowcroft, J., Pias, M., Sharma, R., & Lim, S. (2005). A survey and comparison of peer-to-peer overlay network schemes. IEEE Communications Surveys & Tutorials, vol. 7, no. 2, pp. 72-93.

[2] Guo, D., Kwok, Y. K., Jin, X., & Deng, J. (2016). A performance study of incentive schemes in peer-to-peer file-sharing systems. The Journal of Supercomputing, vol. 72, no. 3, pp. 1152-1178.

[3] Chang, J., Pang, Z., Xu, W., Wang, H., & Yin, G. (2014). An incentive compatible reputation mechanism for P2P systems. The Journal of Supercomputing, vol. 69, no. 3, pp. 1382-1409.

[4] Zhang, Q., Xue, H. F., & Kou, X. D. (2007). An evolutionary game model of resources-sharing mechanism in P2P networks. In Intelligent Information Technology Application, Workshop on (pp. 282-285). IEEE.

[5] Cui, G., Li, M., Wang, Z., Ren, J., Jiao, D., & Ma, J. (2015). Analysis and evaluation of incentive mechanisms in p2p networks: a spatial evolutionary game theory perspective. Concurrency and Computation: Practice and Experience, vol. 27, no. 12, pp. 3044-3064.

[6] Obele, B. O., Ukaegbu, A. I., & Kang, M. (2009). On tackling free-riders in P2P networks. In Advanced Communication Technology, 2009. ICACT 2009. 11th International Conference on (vol. 3, pp. 2084-2089). IEEE.

[7] Rozario, F., Han, Z., & Niyato, D. (2011). Optimization of non-cooperative P2P network from the game theory point of view. In 2011 IEEE Wireless Communications and Networking Conference (pp. 868-873). IEEE.

[8] Atlidakis, V., Roussopoulos, M., & Delis, A. (2014). EnhancedBit: Unleashing the potential of the unchoking policy in the BitTorrent protocol. Journal of Parallel and Distributed Computing, vol. 74, no. 1, pp. 1959-1970.

[9] Manoharan, S., & Ge, T. (2013). A demerit point strategy to reduce free-riding in BitTorrent. Computer Communications, vol. 36, no. 8, pp. 875-880.

[10] Izhak-Ratzin, R. (2010). Improving the BitTorrent protocol using different incentive techniques (Doctoral dissertation, University of California Los Angeles).

[11] Wang, H., Wang, F., Liu, J., Xu, K., & Wu, D. (2013). Torrents on twitter: Explore long-term social relationships in peer-to-peer systems. IEEE Transactions on Network and Service Management, vol. 10, no. 1, pp. 95-104.

[12] Hughes, D., Coulson, G., & Walkerdine, J. (2005). Free riding on Gnutella revisited: the bell tolls?. IEEE distributed systems online, vol. 6, no. 6.

[13] Ren, Y., Li, M., Xiang, Y., Cui, Y., & Sakurai, K. (2013). Evolution of cooperation in reputation system by group-based scheme. The Journal of Supercomputing, vol. 63, no. 1, pp. 171-190.

[14] Alotibi, B., Alarifi, N., Abdulghani, M., & Altoaimy, L. (2019). Overcoming Free-Riding Behavior in Peer-to-Peer Networks Using Points System Approach. Procedia Computer Science, vol. 151, pp. 1060-1065.

[15] Jain, A., & Kumar, S. (2018). FriendShare: A secure and reliable framework for file sharing on network. Journal of Network and Computer Applications, vol. 120, pp. 1-16.

[16] Al-Qurishi, M., Alrubaian, M., Rahman, S. M. M., Alamri, A., & Hassan, M. M. (2018). A prediction system of Sybil attack in social network using deep-regression model. Future Generation Computer Systems, vol. 87, pp. 743-753.

[17] Ramalingam, D., & Chinnaiah, V. (2018). Fake profile detection techniques in large-scale online social networks: A comprehensive review. Computers & Electrical Engineering, vol. 65, pp. 165-177.

[18] Chen, Z., Cheng, Y., Deng, X., Qi, Q., & Yan, X. (2019). Agent incentives of strategic behavior in resource exchange. Discrete Applied Mathematics, vol. 264, pp. 15-25.

[19] Sahoo, S. R., & Gupta, B. B. (2019). Hybrid approach for detection of malicious profiles in twitter. Computers & Electrical Engineering, vol. 76, pp. 65-81.

[20] Zarezade, M., Nourani, E., & Bouyer, A. (2020). Community detection using a new node scoring and synchronous label updating of boundary nodes in social networks. Journal of AI and Data Mining, vol. 8, no. 2, pp. 201-212.

[21] Zhou, R., & Hwang, K. (2007). Powertrust: A robust and scalable reputation system for trusted peer-to-peer computing. IEEE Transactions on parallel and distributed systems, vol. 18, no. 4, pp. 460-473.

[22] Kamvar, S. D., Schlosser, M. T., & Garcia-Molina, H. (2003). The eigentrust algorithm for reputation management in P2P networks. In Proceedings of the 12th international conference on World Wide Web (pp. 640-651). ACM.

[23] Chen, Z., Qiu, Y., Liu, J., & Xu, L. (2011). Incentive mechanism for selfish nodes in wireless sensor networks based on evolutionary game. Computers & Mathematics with Applications, vol. 62, no. 9, pp. 3378-3388.

[24] Wang, Y., Nakao, A., Vasilakos, A. V., & Ma, J. (2011). On the effectiveness of service differentiation based resource-provision incentive mechanisms in dynamic and autonomous P2P networks. Computer Networks, vol. 55, no. 17, pp.3811-3831.

[25] Figueiredo, D., Shapiro, J., & Towsley, D. (2005). Incentives to promote availability in peer-to-peer anonymity systems. In 13TH IEEE International Conference on Network Protocols (ICNP'05) (pp. 12-pp). IEEE.

[26] Lian, Q., Yu, P., Yang, M., Zhang, Z., Dai, Y., Li, X., & Yu, R. P. (2007). Robust incentives via multi-level tit-for-tat, Currency and Computation: practice and experience, vol. 20, no. 2, pp. 167-178

[27] Centeno, R., Billhardt, H., & Hermoso, R. (2013). Persuading agents to act in the right way: An incentive-based approach. Engineering Applications of Artificial Intelligence, vol. 26, no. 1, pp. 198-210.

[28] Mahini, H., Dehghan, M., Navidi, H., & Masoud Rahmani, A. (2016). GaMe‐PLive: a new game theoretic mechanism for P2P live video streaming. International Journal of Communication Systems, vol. 29, no. 6, pp. 1187-1203.

[29] Mahini, H., Dehghan, M., Navidi, H., & Rahmani, A. M. (2017). Peer-assisted video streaming based on network coding and Beer-Quiche game. AEU-International Journal of Electronics and Communications, vol. 73, pp. 34-45.

[30] Douceur, J. R. (2002). The sybil attack. In International Workshop on Peer-to-Peer Systems (pp. 251-260). Springer Berlin Heidelberg.

[31] Xu, L., Chainan, S., Takizawa, H., & Kobayashi, H. (2010). Resisting sybil attack by social network and network clustering. In Applications and the Internet (SAINT), 2010 10th IEEE/IPSJ International Symposium on (pp. 15-21). IEEE.

[32] Rowaihy, H., Enck, W., McDaniel, P., & La Porta, T. (2007, May). Limiting sybil attacks in structured p2p networks. In IEEE INFOCOM 2007-26th IEEE International Conference on Computer Communications (pp. 2596-2600). IEEE.

[33] Dinger, J., & Hartenstein, H. (2006). Defending the sybil attack in P2P networks: Taxonomy, challenges, and a proposal for self-registration. In First International Conference on Availability, Reliability and Security (ARES'06) (pp. 8-pp). IEEE.

[34] Trifa, Z., & Khemakhem, M. (2012). Mitigation of Sybil Attacks in Structured P2P Overlay Networks. In Semantics, Knowledge and Grids (SKG), 2012 Eighth International Conference on (pp. 245-248). IEEE.

[35] Yu, H., Kaminsky, M., Gibbons, P. B., & Flaxman, A. D. (2008). Sybilguard: defending against sybil attacks via social networks. IEEE/ACM Transactions on networking, vol. 16, no. 3, pp. 576-589.

[36] Shareh, M. B., Navidi, H., Javadi, H. H. S., & HosseinZadeh, M. (2019). Preventing Sybil attacks in P2P file sharing networks based on the evolutionary game model. Information Sciences, vol. 470, pp. 94-108.

[37] Azzedin, F., & Yahaya, M. (2016). Modeling BitTorrent choking algorithm using game theory. Future Generation Computer Systems, vol. 55, pp. 255-265.

[38] Pavel, L. (2012). Game theory for control of optical networks. Springer Science & Business Media.

[39] Feng, H., Zhang, S., Liu, C., Yan, J., & Zhang, M. (2008). P2P incentive model on evolutionary game theory. In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (pp. 1-4). IEEE.

[40] Nisan, N., Roughgarden, T., Tardos, E., & Vazirani, V. V. (Eds.). (2007). Algorithmic game theory (Vol. 1). Cambridge: Cambridge University Press.

[41] Narahari, Y. (2014). Game theory and mechanism design (Vol. 4). World Scientific, IISc Press.

[42] Alexander, J. M. (2002). Evolutionary game theory. Sidney, Stanford Press.

[43] Szabó, G., & Vukov, J. (2004). Cooperation for volunteering and partially random partnerships. Physical Review E, 69(3 Pt 2):036107.

[44] Szabó, G., & Tőke, C. (1998). Evolutionary prisoner’s dilemma game on a square lattice. Physical Review E, vol. 58, no. 1, pp. 69-73.