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Article
Sybil tolerance and probabilistic databases to compute web services trust
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Zohra Saoud, Université Claude Bernard Lyon 1
  • Noura Faci, Université Claude Bernard Lyon 1
  • Zakaria Maamar, Zayed University
  • Djamal Benslimane, Université Claude Bernard Lyon 1
Document Type
Conference Proceeding
Publication Date
1-1-2015
Abstract

© Springer International Publishing Switzerland 2015. This paper discusses how Sybil attacks can undermine trust management systems and how to respond to these attacks using advanced techniques such as credibility and probabilistic databases. In such attacks end-users have purposely different identities and hence, can provide inconsistent ratings over the same Web Services. Many existing approaches rely on arbitrary choices to filter out Sybil users and reduce their attack capabilities. However this turns out inefficient. Our approach relies on non-Sybil credible users who provide consistent ratings over Web services and hence, can be trusted. To establish these ratings and debunk Sybil users techniques such as fuzzy-clustering, graph search, and probabilistic databases are adopted. A series of experiments are carried out to demonstrate robustness of our trust approach in presence of Sybil attacks.

ISBN
9783319231341
Publisher
Springer Verlag
Disciplines
Keywords
  • Credibility,
  • Fuzzy clustering,
  • Sybil,
  • Trust,
  • Web service
Scopus ID
84944564960
Indexed in Scopus
Yes
Open Access
No
https://doi.org/10.1007/978-3-319-23135-8_31
Citation Information
Zohra Saoud, Noura Faci, Zakaria Maamar and Djamal Benslimane. "Sybil tolerance and probabilistic databases to compute web services trust" Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9282 (2015) p. 458 - 471 ISSN: <a href="https://v2.sherpa.ac.uk/id/publication/issn/0302-9743" target="_blank">0302-9743</a>
Available at: http://works.bepress.com/zakaria-maamar/261/