Abstract

Privacy is an important issue in the collaborative data mining since privacy concerns may prevent the parties from directly sharing the data and some types of information about the data. How multiple parties collaboratively conduct data mining without breaching data privacy presents a challenge. This paper seeks to investigate solutions for privacy-preserving support vector machine classification which is one of data mining tasks. The goal is to obtain accurate classification results without disclosing private data.

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