Contrasting False Identities in Social Networks by Trust Chains and Biometric Reinforcement

Francesco Buccafurri (1) , Gianluca Lax (1) , Denis Migdal (2) , Serena Nicolazzo (1) , Antonino Nocera (1) , Christophe Rosenberger (2)

1 Universita Mediterranea of Reggio Calabria [Reggio Calabria]
2 Equipe SAFE - Laboratoire GREYC - UMR6072

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.

Mots clés: Social networks; trust; keystroke dynamics

Domaines: Cryptographie et sécurité [cs.CR]; Réseaux sociaux et d'information [cs.SI]

Francesco Buccafurri, Gianluca Lax, Denis Migdal, Serena Nicolazzo, Antonino Nocera, et al.. Contrasting False Identities in Social Networks by Trust Chains and Biometric Reinforcement. CyberWorlds, Sep 2017, Chester, United Kingdom. ⟨hal-01589753⟩