Privacy-preserving agent-based distributed data clustering

Article type: Research Article

Authors: da Silva, Josenildo Costa | Klusch, Matthias | Lodi, Stefano | Moro, Gianluca

Affiliations: Deduction and Multiagent Systems, German Research Center for Artificial Intelligence, Stuhlsatzenhausweg 3, 66123 Saarbrücken, Germany | Department of Electronics, Computer Science, and Systems, University of Bologna, Viale Risorgimento 2, 40136 Bologna BO, Italy | Department of Electronics, Computer Science and Systems, University of Bologna, Via Venezia 52, 47023 Cesena FC, Italy

Note: [] Corresponding author. Tel.: +39 051 2093560; Fax: +39 051 2093540; E-mail: [email protected]

Abstract: A growing number of applications in distributed environment involve very large data sets that are inherently distributed among a large number of autonomous sources over a network. The demand to extend data mining technology to such distributed data sets has motivated the development of several approaches to distributed data mining and knowledge discovery, of which only a few make use of agents. We briefly review existing approaches and argue for the potential added value of using agent technology in the domain of knowledge discovery, discussing both issues and benefits. We also propose an approach to distributed data clustering, outline its agent-oriented implementation, and examine potential privacy violating attacks which agents may incur.

Keywords: Distributed data mining, data clustering, data security, Multi-Agent System, data privacy

Journal: Web Intelligence and Agent Systems: An international journal, vol. 4, no. 2, pp. 221-238, 2006