A Performance Study of Secure Data Mining on the Cell Processor

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Author(s): Hong Wang (Tohoku University, Japan), Hiroyuki Takizawa (Tohoku University, Japan)and Hiroaki Kobayashi (Tohoku University, Japan)
Copyright: 2012
Pages: 13
Source title: Cyber Crime: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-61350-323-2.ch416

Keywords: Digital Crime & Forensics / Information Science Reference / IT Security and Ethics / Security & Forensics

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Abstract

This article examines the potential of the Cell processor as a platform for secure data mining on the future volunteer computing systems. Volunteer computing platforms have the potential to provide massive computing power. However, privacy and security concerns prevent using volunteer computing for data mining of sensitive data. The Cell processor comes with hardware security features. The secure volunteer data mining can be achieved by using those hardware security features. In this article, we present a general security scheme for the volunteer computing, and a secure parallelized K-Means clustering algorithm for the Cell processor. We also evaluate the performance of the algorithm on the Cell secure system simulator. Evaluation results indicate that the proposed secure data clustering outperforms a non-secure clustering algorithm on the general purpose CPU, but incurs a huge performance overhead introduced by the decryption process of the Cell security features. Possible optimization for the secure K-Means clustering is discussed.

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A Performance Study of Secure Data Mining on the Cell Processor

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