Distributed Online Social Networks (DOSNs) have been recently proposed as an alternative to centralized solutions to allow a major control of the users over their own data. Since there is no centralized service provider which decides the term of service, the DOSNs infrastructure exploits users’ devices to take on the online social network services. In this paper, we propose a data allocation strategy for DOSNs which exploits the privacy policies of the users to increase the availability of the users’ contents without diverging from their privacy preferences. A set of replicas of the profile’s content of a user U are stored on the devices of other users who are entitled to access the profile according to U’s privacy policies. The experimental results obtained from the simulations on traces taken from a real social network show the effectiveness of our approach.

De Salve, A., Mori, P., Ricci, L., Al-Aaridhi, R., Graffi, K. (2016). Privacy-preserving data allocation in decentralized online social networks. In M. Jelasity, E. Kalyvianaki (a cura di), Distributed Applications and Interoperable Systems (pp. 47-60). Springer Verlag [10.1007/978-3-319-39577-7_4].

Privacy-preserving data allocation in decentralized online social networks

De Salve, Andrea
;
2016-01-01

Abstract

Distributed Online Social Networks (DOSNs) have been recently proposed as an alternative to centralized solutions to allow a major control of the users over their own data. Since there is no centralized service provider which decides the term of service, the DOSNs infrastructure exploits users’ devices to take on the online social network services. In this paper, we propose a data allocation strategy for DOSNs which exploits the privacy policies of the users to increase the availability of the users’ contents without diverging from their privacy preferences. A set of replicas of the profile’s content of a user U are stored on the devices of other users who are entitled to access the profile according to U’s privacy policies. The experimental results obtained from the simulations on traces taken from a real social network show the effectiveness of our approach.
2016
Settore INF/01 - Informatica
978-3-319-39576-0
978-3-319-39577-7
De Salve, A., Mori, P., Ricci, L., Al-Aaridhi, R., Graffi, K. (2016). Privacy-preserving data allocation in decentralized online social networks. In M. Jelasity, E. Kalyvianaki (a cura di), Distributed Applications and Interoperable Systems (pp. 47-60). Springer Verlag [10.1007/978-3-319-39577-7_4].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/354911
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