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Contrasting false identities in social networks by trust chains and biometric reinforcement

  • Francesco Buccafurri
  • , Gianluca Lax
  • , Denis Migdal
  • , Serena Nicolazzo
  • , Antonino Nocera
  • , Christophe Rosenberger

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Fake identities and identity theft are issues whose relevance is increasing in the social network domain. This paper deals with this problem by proposing an innovative approach which combines a collaborative mechanism implementing a trust graph with keystroke-dynamic-recognition techniques to trust identities. The trust of each node is computed on the basis of neighborhood recognition and behavioral biometric support. The model leverages the word of mouth propagation and a settable degree of redundancy to obtain robustness. Experimental results show the benefit of the proposed solution even if attack nodes are present in the social network.

Original languageEnglish
Title of host publicationProceedings - 2017 International Conference on Cyberworlds, CW 2017 - in cooperation with
Subtitle of host publicationEurographics Association International Federation for Information Processing ACM SIGGRAPH
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages17-24
Number of pages8
ISBN (Electronic)9781538620892
DOIs
Publication statusPublished - 27 Nov 2017
Externally publishedYes
Event2017 International Conference on Cyberworlds, CW 2017 - Chester, United Kingdom
Duration: 20 Sept 201722 Sept 2017

Publication series

NameProceedings - 2017 International Conference on Cyberworlds, CW 2017 - in cooperation with: Eurographics Association International Federation for Information Processing ACM SIGGRAPH
Volume2017-January

Conference

Conference2017 International Conference on Cyberworlds, CW 2017
Country/TerritoryUnited Kingdom
CityChester
Period20/09/1722/09/17

Keywords

  • Keystroke dynamics
  • Social networks
  • Trust

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