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Reseach Article

VoteTrust: A System to Defend against Social Network Sybils in Facebook

by Priyanka, Deepthi K.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 11
Year of Publication: 2016
Authors: Priyanka, Deepthi K.
10.5120/ijca2016909854

Priyanka, Deepthi K. . VoteTrust: A System to Defend against Social Network Sybils in Facebook. International Journal of Computer Applications. 142, 11 ( May 2016), 1-5. DOI=10.5120/ijca2016909854

@article{ 10.5120/ijca2016909854,
author = { Priyanka, Deepthi K. },
title = { VoteTrust: A System to Defend against Social Network Sybils in Facebook },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 11 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number11/24937-2016909854/ },
doi = { 10.5120/ijca2016909854 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:44:40.890718+05:30
%A Priyanka
%A Deepthi K.
%T VoteTrust: A System to Defend against Social Network Sybils in Facebook
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 11
%P 1-5
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Sybil attack is one where an user creates multiple Duplicate or fake identities to compromise the running of the system. Online social networks(OSN) suffers from the creation of fake accounts that introduce fake product reviews, malware and spam, existing defenses focus on using the social graph structure to isolate fakes. This paper presents VoteTrust- a salable defense system that further leverages user level activities. VoteTrust models the friend invitation interactions among users as a directed, signed graph, and it uses a Sybil detection algorithm to find Sybil users, who have more chances of rejecting friend request than normal users. Facebook operates a leading real-name social networking internet platform, which enables users to connect and communicate with each other, share information, and to enjoy a wide range of other features and services. Through evaluating Facebook social network, it can be shown that VoteTrust will able to prevent Sybil users from generating many unsolicited friend requests.

References
  1. Why social media is important.
  2. John R Douceur. The sybil attack. In Peer-to-peer Systems, pages 251–260. Springer, 2002.
  3. Kevin Hoffman, David Zage, and Cristina Nita-Rotaru. A survey of attack and defense techniques for reputation systems. ACM Computing Surveys (CSUR), 42(1):1, 2009.
  4. AndreasMKaplan and Michael Haenlein. Users of the world, unite! the challenges and opportunities of social media. Business horizons, 53(1):59–68, 2010.
  5. Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon. What is twitter, a social network or a news media? In Proceedings of the 19th international conference on World wide web, pages 591–600. ACM, 2010.
  6. Brian Neil Levine, Clay Shields, and N Boris Margolin. A survey of solutions to the sybil attack. University of Massachusetts Amherst, Amherst, MA, 2006.
  7. Daniel Nations. n.d. ”what is social media? what are social media sites?”.
  8. James Newsome, Elaine Shi, Dawn Song, and Adrian Perrig. The sybil attack in sensor networks: analysis & defenses. In Proceedings of the 3rd international symposium on Information processing in sensor networks, pages 259–268. ACM, 2004.
  9. Al-Sakib Khan Pathan. Security of self-organizing networks: MANET, WSN, WMN, VANET. CRC press, 2010.
  10. Gianluca Stringhini, Christopher Kruegel, and Giovanni Vigna. Detecting spammers on social networks. In Proceedings of the 26th Annual Computer Security Applications Conference, pages 1–9. ACM, 2010.
  11. Jilong Xue, Zhi Yang, Xiaoyong Yang, Xiao Wang, Lijiang Chen, and Yafei Dai. Votetrust: Leveraging friend invitation graph to defend against social network sybils. In INFOCOM, 2013 Proceedings IEEE, pages 2400–2408. IEEE, 2013.
  12. Z. Yang, J. Xue, X. Yang, X. Wang, and Y. Dai. Votetrust: Leveraging friend invitation graph to defend against social network sybils. Dependable and Secure Computing, IEEE Transactions on, PP(99):1–1, 2015.
  13. Zhi Yang, Christo Wilson, Xiao Wang, Tingting Gao, Ben Y Zhao, and Yafei Dai. Uncovering social network sybils in the wild. ACM Transactions on Knowledge Discovery from Data (TKDD), 8(1):2, 2014.
  14. Kuan Zhang, Xiaohui Liang, Rongxing Lu, and Xuemin Shen. Sybil attacks and their defenses in the internet of things. Internet of Things Journal, IEEE, 1(5):372–383, 2014.
  15. Xiaokuan Zhang, Haizhong Zheng, Xiaolong Li, Suguo Du, and Haojin Zhu. You are where you have been: Sybil detection via geo-location analysis in osns. In Global Communications Conference (GLOBECOM), 2014 IEEE, pages 698–703. IEEE, 2014.
Index Terms

Computer Science
Information Sciences

Keywords

Online social networks(OSN) Security Sybil attack Sybil detection Unsolicited friend requests