Identification of Sybil Attack on Social Networks
 |
International Journal of Computer Trends and Technology (IJCTT) | 
|
| © 2016 by IJCTT Journal | ||
| Volume-34 Number-2 |
||
| Year of Publication : 2016 | ||
| Authors : Dr.J.I.Sheeba, V.Saranya, Dr.S.Pradeep Devaneyan | ||
| DOI : 10.14445/22312803/IJCTT-V34P112 |
Dr.J.I.Sheeba, V.Saranya, Dr.S.Pradeep Devaneyan "Identification of Sybil Attack on Social Networks". International Journal of Computer Trends and Technology (IJCTT) V34(2):68-74, April 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Social networks play a vital role in daily
life since it is vulnerable to many security attacks,
namely Sybil attacks. The Sybil attack is an attack
where a single user can create a many bogus
identity to impersonate like others. The Sybil node in
social networking is used for criminal activities such
as stealing legitimate information about the user
present in social networks it will lead to system
degradation process. Since the Sybil identification
algorithm does not provide a complete solution to
detect the Sybil node in social networks. In order to
overcome these drawbacks Sybil defender algorithm
gets deployed in a proposed framework to detect the
Sybil node in social networks. The Sybil defender
algorithm will perform a limited number of random
walk on social networks. Sybil defender is a
combination of both Sybil identification algorithm
and Sybil community detection algorithm. A Sybil
identification algorithm is used to detect the Sybil
node and Sybil community detection algorithm is
used to detect Sybil community around the Sybil
node in the social networks. By comparing with the
existing approaches Sybil node will be effectively
detected using Sybil defender algorithm. This
proposed and existing works are measured in terms
of evaluation metrics namely non-trustworthy rate,
detection rate, packet loss, end to end delivery.
References
[1] Rakesh G.V et.al “A Survey Of Techniques To Defend
Against Sybil Attacks In Social Networks” in International
Journal of Advanced Research in Computer and Communication
Engineering Vol. 3, Issue 5, May 2014
[2] Zied Trifa “Sybil Nodes as a Mitigation Strategy against Sybil
Attack” in International Workshop on Secure Peer-to-Peer
Intelligent Networks & Systems (SPINS-2014).
[3] Jochen Dinger and Hannes Hartenstein, “Defending the Sybil
Attack in P2P Networks: Taxonomy, Challenges, and a Proposal
for Self Registration”, In Proc. First International Conference on
Availability, Reliability and Security (ARES 2006), Vienna,
Austria, 2006, pp. 756-763.
[4] RoopaliGarg” Comparison between Sybil Attack Detection
Techniques: Lightweight and Robust in International Journal of
Advanced Research in Electrical, electronics and
Instrumentation” Engineering Vol. 3, Issue 2, February 2014.
[5]Guojun Wang “Neighbor Similarity Trust against Sybil Attack
in P2P E-Commerce”in IEEE transactions on parallel and
distributed systems, vol. 26, no. 3, March 2015.
[6] Ankush Tehale “Parental control algorithm for Sybil detection
in distributed p2p networks” in International Journal of Scientific
and Research Publications, Volume 2, Issue 5, May 2012.
[7] Haifeng Yu, M. Kaminsky, P. B. Gibbons, A. Flaxman,
“SybilGuard: Defending Against Sybil Attacks via Social
Networks”, in Proc. ACM SIGCOMM, 2006, pp. 267–278.
[8]Haifeng Yu, Phillip B. Gibbons, M. Kaminsky, F. Xiao,
“SybilLimit: A Near-Optimal Social Network Defense against
Sybil Attacks”, in Proc. IEEE/ACM transactions on networking,
vol. 18, no. 3, June 2010.
[9] N. Tran, J. Li, L. Subramanian, and S.S. Chow, “Optimal
Sybil Resilient Node Admission Control,” Proc. IEEE infocom,
2011.
[9]A. Cheng, and E. Friedman,“Sybil proof reputation
mechanisms”, In Proc. ACM SIGCOMM Workshop on
Economics of Peer-to-Peer Systems”, 2005, ACM Press, pp. 128-
132.
[10] G. Danezis and P. Mit, “Sybil infer: Detecting Sybil Nodes
Using Social Networks,” Proc. Network and Distributed System
Security Symp. (NDSS), 2009.
[11] A. Kurve and G. Kesidis, “Sybil Detection via Distributed
Sparse Cut Monitoring”, in Proc. ICC 2011, pp. 1-6.
[12] C. Hota, J. Lindqvist, K. Karvonen, A. Ylä-Jääski, Mohan
C.K.J“Safeguarding Against Sybil Attacks via Social Networks
and Multipath Routing”, in Proc. NAS 2007,pp. 122 – 132.
[13] G. Kesidis, A. Tangpong and C. Griffin, “A Sybil-proof
referral system based on multiplicative reputation chains,” IEEE
comm. letters, pp. 862- 864, nov. 2009.
[14] J. Douceur” The Sybil Attack. In 1st International Workshop
on Peer-to -peer Systems” (IPTPS ’02). Springer,, 2002, pp. 251-
260.
[15] Samidha Nagdeve “Sybil attack detection on peer to peer
network based on enchanced Sybil –resilient protocol “in
international journal for scientific and research and development..
[16] Hengkui Wu” SybilBF: Defending against Sybil Attacks via
Bloom Filters in ETRI Journal, Volume 33, Number 5, October
2011
[17] Wei , Fengyuan Xu SybilDefender: “A Defense Mechanism
for Sybil Attacks in Large Social Networks” in IEEE transactions
on parallel and distributed systems, vol. 24, no. 12, December
2013
[18] Saranya V et.al,”Detection of Sybil attack on social networks
using Sybil defender algorithm” International journal of control
theory and applications (In press).
Keywords
Sybil attack, Sybil identification
algorithm, Sybil defender algorithm, Social
networks, Sybil community detection algorithm.