Year: 2018
Type: dissertation
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\n\ntested 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\n\nconsistent 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\n\nslightly 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\n\nlarge portions of the input graphs and its accuracy among the portion of the graphs it does recognize becomes lower than that of DownhillFlow.
Author: M. T. Bradley
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2887497892