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

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

Risultato della ricerca: Capitolo in libro/report/atti di convegnoContributo a conferenzapeer 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.

Lingua originaleInglese
Titolo della pubblicazione ospiteProceedings - 2017 International Conference on Cyberworlds, CW 2017 - in cooperation with
Sottotitolo della pubblicazione ospiteEurographics Association International Federation for Information Processing ACM SIGGRAPH
EditoreInstitute of Electrical and Electronics Engineers Inc.
Pagine17-24
Numero di pagine8
ISBN (elettronico)9781538620892
DOI
Stato di pubblicazionePubblicato - 27 nov 2017
Pubblicato esternamente
Evento2017 International Conference on Cyberworlds, CW 2017 - Chester, United Kingdom
Durata: 20 set 201722 set 2017

Serie di pubblicazioni

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???2017 International Conference on Cyberworlds, CW 2017
Paese/TerritorioUnited Kingdom
CittàChester
Periodo20/09/1722/09/17

Fingerprint

Entra nei temi di ricerca di 'Contrasting false identities in social networks by trust chains and biometric reinforcement'. Insieme formano una fingerprint unica.

Cita questo