Abstract
Data mining is becoming an increasingly important technology for the information society. Due to limited computational resources of data owners and the prevalence of cloud computing, outsourced data mining is becoming more and more attractive. The privacy and security issues are becoming outstanding recently. Though the existing model of cloud computing consists of multiple data owners, there is little consideration for the collaboration between them. However, such collaboration is necessary with the trend of data partition among different entities nowadays. Besides, most of the existing work is based on the semi-honest cloud assumption and cannot deal with the malicious cloud situation well. In this paper, we explore the secure and practical outsourced collaborative data mining scheme in cloud computing scenarios. We design a simple framework for it and propose several enhanced frameworks and detailed schemes in an incremental way with stronger security considerations. The final framework utilizes trusted computing technology to design the scheme under the malicious cloud assumption. Finally, we give a summary of security and efficiency analysis of them. As a case of study, we prove the correctness of the frameworks with three classical methods KNN, K-means and SVM respectively in such outsourced collaborative computing scenario.
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