DocumentCode
2520365
Title
Resisting Sybil Attack By Social Network and Network Clustering
Author
Xu, Ling ; Chainan, Satayapiwat ; Takizawa, Hiroyuki ; Kobayashi, Hiroaki
Author_Institution
Grad. Sch. of Inf. Sci., Tohoku Univ., Sendai, Japan
fYear
2010
fDate
19-23 July 2010
Firstpage
15
Lastpage
21
Abstract
Peer to peer (P2P) systems are extremely vulnerable to Sybil attacks, in which a malicious user controls a large number of Sybil peers to collude to break the system laws. This paper proposes a distributed algorithm, named Sybil Resisting Network Clustering (SRNC), to resist the Sybil attack by preventing honest peers from communicating with Sybil Peers. SRNC is based on a social network model. In this model, honest peers and Sybil peers can be largely classified into two clusters, connected by a small number of edges, called attack edges. SRNC tries to explicitly detect attack edges, and then prohibits the communication over the detected edges. The performance of SRNC is evaluated by theoretical analysis and simulations. In particular, SRNC ensures theoretically that honest peers totally accept O(|AE|) Sybil peers. This is a O(log(n)) times improvement over SybilLimit, one of the conventional representative Sybil resisting algorithms, where n is the number of peers and |AE| is the number of attack edges in the system. The performance is then evaluated by simulations on data sets of real world social networks.
Keywords
computational complexity; distributed algorithms; peer-to-peer computing; security of data; social networking (online); Sybil attacks; Sybil peers; Sybil resisting network clustering; distributed algorithm; malicious user; peer to peer systems; social network model; Clustering algorithms; Data models; Image edge detection; Peer to peer computing; Protocols; Security; Social network services; p2p; social network; sybil;
fLanguage
English
Publisher
ieee
Conference_Titel
Applications and the Internet (SAINT), 2010 10th IEEE/IPSJ International Symposium on
Conference_Location
Seoul
Print_ISBN
978-1-4244-7526-1
Electronic_ISBN
978-0-7695-4107-5
Type
conf
DOI
10.1109/SAINT.2010.32
Filename
5598178
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