ECAI 2004 Conference Paper

[PDF] [full paper] [prev] [tofc] [next]

Inference Attacks in Peer-to-Peer Homogeneous Distributed Data Mining

Josenildo Costa da Silva, Matthias Klusch, Stefano Lodi, Gianluca Moro

Agent technology could provide a computing paradigm which naturally fits distributed data mining environments. In particular, spontaneous formation of peer-to-peer agent-based data mining systems seems a plausible scenario in years to come. However, the emergence of peer-to-peer environments further aggravates privacy and security concerns that arise when performing data mining tasks. We analyze potential threats to data privacy in a peer-to-peer agent-based distributed data mining scenario under the hypothesis that all the distributed datasets follow the same schema, and discuss inference attacks which could compromise data privacy in a peer-to-peer distributed clustering scheme known as KDEC.

Keywords: inference attack, peer-to-peer, distributed data mining, privacy, data clustering

Citation: Josenildo Costa da Silva, Matthias Klusch, Stefano Lodi, Gianluca Moro: Inference Attacks in Peer-to-Peer Homogeneous Distributed Data Mining. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.450-454.


[prev] [tofc] [next]


ECAI-2004 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Universitat Politècnica de València on behalf of Asociación Española de Inteligencia Artificial (AEPIA) and Associació Catalana d'Intel-ligència Artificial (ACIA).