Istituto di Scienza e Tecnologie dell'Informazione     
Giannotti F., Lakshmanan L. V., Monreale A., Pedreschi D., Wang H. Privacy-preserving mining of association rules from outsourced transaction databases. Extended abstract. In: SEBD 2012 - Twentieth Italian Symposium on Advanced Database Systems (Venice, Italy, 24-27 June 2012). Atti, pp. 233 - 242. Nicola Ferro, Letizia Tanca (eds.). Edizioni Libreria Progetto and the authors, 2012.
Spurred by developments such as cloud computing, there has been considerable recent interest in the paradigm of data mining-as-service. A company (data owner) lacking in expertise or computational resources can outsource its mining needs to a third party service provider (server). However, both the items and the association rules of the outsourced database are considered private property of the corporation (data owner). To protect corporate privacy,the data owner transforms its data and ships it to the server, sends mining queries to the server, and recovers the true patterns from the extracted patterns received from the server. In this paper, we study the problem of outsourcing the association rule mining task within a corporate privacy-preserving framework. We propose a scheme for privacy preserving outsourced mining and show that the owner can recover the true patterns as well as their support by maintaining a compact synopsis.
URL: http://sebd2012.dei.unipd.it/documents/188475/289b3a84-87e8-4fae-98f1-6c6d8dafb833
Subject Privacy
E.3 Data Encryption

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