Designs to account for trust in social network-based Sybil defenses

Abedelaziz Mohaisen; Nicholas Hopper; Yongdae Kim

doi:10.1145/1866307.1866407

Designs to account for trust in social network-based Sybil defenses

Abedelaziz Mohaisen, Nicholas Hopper, Yongdae Kim

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Social network-based Sybil defenses exploit the trust exhibited in social graphs to detect Sybil nodes that disrupt an algorithmic property (i.e., the fast mixing) in these graphs. The performance of these defenses depends on the quality of the algorithmic property and assuming a strong trust model in the underlying graph. While it is natural to think of trust value associated with the social graphs, Sybil defenses have used the social graphs without this consideration. In this paper we study paramagnetic designs to tune the performance of Sybil defenses by accounting for trust in social graphs and modeling the trust as modified random walks. Our designs are motivated by the observed relationship between the algorithmic property required for the defenses to perform well and a hypothesized trust value in the underlying graphs.

Original language	English (US)
Title of host publication	CCS'10 - Proceedings of the 17th ACM Conference on Computer and Communications Security
Pages	714-716
Number of pages	3
DOIs	https://doi.org/10.1145/1866307.1866407
State	Published - 2010
Event	17th ACM Conference on Computer and Communications Security, CCS'10 - Chicago, IL, United States Duration: Oct 4 2010 → Oct 8 2010

Publication series

Name	Proceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)	1543-7221

Other

Other	17th ACM Conference on Computer and Communications Security, CCS'10
Country/Territory	United States
City	Chicago, IL
Period	10/4/10 → 10/8/10

Keywords

Social networks
Sybil attack
Trust

Publisher link

10.1145/1866307.1866407

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Designs to account for trust in social network-based Sybil defenses. / Mohaisen, Abedelaziz; Hopper, Nicholas; Kim, Yongdae.
CCS'10 - Proceedings of the 17th ACM Conference on Computer and Communications Security. 2010. p. 714-716 (Proceedings of the ACM Conference on Computer and Communications Security).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mohaisen, A, Hopper, N & Kim, Y 2010, Designs to account for trust in social network-based Sybil defenses. in CCS'10 - Proceedings of the 17th ACM Conference on Computer and Communications Security. Proceedings of the ACM Conference on Computer and Communications Security, pp. 714-716, 17th ACM Conference on Computer and Communications Security, CCS'10, Chicago, IL, United States, 10/4/10. https://doi.org/10.1145/1866307.1866407

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abstract = "Social network-based Sybil defenses exploit the trust exhibited in social graphs to detect Sybil nodes that disrupt an algorithmic property (i.e., the fast mixing) in these graphs. The performance of these defenses depends on the quality of the algorithmic property and assuming a strong trust model in the underlying graph. While it is natural to think of trust value associated with the social graphs, Sybil defenses have used the social graphs without this consideration. In this paper we study paramagnetic designs to tune the performance of Sybil defenses by accounting for trust in social graphs and modeling the trust as modified random walks. Our designs are motivated by the observed relationship between the algorithmic property required for the defenses to perform well and a hypothesized trust value in the underlying graphs.",

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AU - Hopper, Nicholas

AU - Kim, Yongdae

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N2 - Social network-based Sybil defenses exploit the trust exhibited in social graphs to detect Sybil nodes that disrupt an algorithmic property (i.e., the fast mixing) in these graphs. The performance of these defenses depends on the quality of the algorithmic property and assuming a strong trust model in the underlying graph. While it is natural to think of trust value associated with the social graphs, Sybil defenses have used the social graphs without this consideration. In this paper we study paramagnetic designs to tune the performance of Sybil defenses by accounting for trust in social graphs and modeling the trust as modified random walks. Our designs are motivated by the observed relationship between the algorithmic property required for the defenses to perform well and a hypothesized trust value in the underlying graphs.

AB - Social network-based Sybil defenses exploit the trust exhibited in social graphs to detect Sybil nodes that disrupt an algorithmic property (i.e., the fast mixing) in these graphs. The performance of these defenses depends on the quality of the algorithmic property and assuming a strong trust model in the underlying graph. While it is natural to think of trust value associated with the social graphs, Sybil defenses have used the social graphs without this consideration. In this paper we study paramagnetic designs to tune the performance of Sybil defenses by accounting for trust in social graphs and modeling the trust as modified random walks. Our designs are motivated by the observed relationship between the algorithmic property required for the defenses to perform well and a hypothesized trust value in the underlying graphs.

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Designs to account for trust in social network-based Sybil defenses

Abstract

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