An Investigation of Flow-based Algorithms for Sybil Defense
abstract: Distributed systems are prone to attacks, called Sybil attacks, wherein an adversary may generate an unbounded number of bogus identities to gain control over the system. In this thesis, an algorithm, DownhillFlow, for mitigating such attacks is presented and tested experimentally. The tr...
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ndltd-asu.edu-item-501112018-08-02T03:01:05Z An Investigation of Flow-based Algorithms for Sybil Defense abstract: Distributed systems are prone to attacks, called Sybil attacks, wherein an adversary may generate an unbounded number of bogus identities to gain control over the system. In this thesis, an algorithm, DownhillFlow, for mitigating such attacks is presented and tested experimentally. The trust rankings produced by the algorithm are significantly better than those of the distributed SybilGuard protocol and only slightly worse than those of the best-known Sybil defense algorithm, ACL. The results obtained for ACL are consistent with those obtained in previous studies. The running times of the algorithms are also tested and two results are obtained: first, DownhillFlow’s running time is found to be significantly faster than any existing algorithm including ACL, terminating in slightly over one second on the 300,000-node DBLP graph. This allows it to be used in settings such as dynamic networks as-is with no additional functionality needed. Second, when ACL is configured such that it matches DownhillFlow’s speed, it fails to recognize large portions of the input graphs and its accuracy among the portion of the graphs it does recognize becomes lower than that of DownhillFlow. Dissertation/Thesis Bradley, Michael (Author) Bazzi, Rida (Advisor) Richa, Andrea (Committee member) Sen, Arunabha (Committee member) Arizona State University (Publisher) Computer science eng 81 pages Masters Thesis Computer Science 2018 Masters Thesis http://hdl.handle.net/2286/R.I.50111 http://rightsstatements.org/vocab/InC/1.0/ 2018 |
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English |
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Dissertation |
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Computer science |
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Computer science An Investigation of Flow-based Algorithms for Sybil Defense |
description |
abstract: Distributed systems are prone to attacks, called Sybil attacks, wherein an adversary may generate an unbounded number of bogus identities to gain control over the system. In this thesis, an algorithm, DownhillFlow, for mitigating such attacks is presented and
tested experimentally. The trust rankings produced by the algorithm are significantly better than those of the distributed SybilGuard protocol and only slightly worse than those of the best-known Sybil defense algorithm, ACL. The results obtained for ACL are
consistent with those obtained in previous studies. The running times of the algorithms are also tested and two results are obtained: first, DownhillFlow’s running time is found to be significantly faster than any existing algorithm including ACL, terminating in
slightly over one second on the 300,000-node DBLP graph. This allows it to be used in settings such as dynamic networks as-is with no additional functionality needed. Second, when ACL is configured such that it matches DownhillFlow’s speed, it fails to recognize
large portions of the input graphs and its accuracy among the portion of the graphs it does recognize becomes lower than that of DownhillFlow. === Dissertation/Thesis === Masters Thesis Computer Science 2018 |
author2 |
Bradley, Michael (Author) |
author_facet |
Bradley, Michael (Author) |
title |
An Investigation of Flow-based Algorithms for Sybil Defense |
title_short |
An Investigation of Flow-based Algorithms for Sybil Defense |
title_full |
An Investigation of Flow-based Algorithms for Sybil Defense |
title_fullStr |
An Investigation of Flow-based Algorithms for Sybil Defense |
title_full_unstemmed |
An Investigation of Flow-based Algorithms for Sybil Defense |
title_sort |
investigation of flow-based algorithms for sybil defense |
publishDate |
2018 |
url |
http://hdl.handle.net/2286/R.I.50111 |
_version_ |
1718715891000016896 |