Privately Computing a Distributed k-nn Classifier
نویسندگان
چکیده
The ability of databases to organize and share data often raises privacy concerns. Data warehousing combined with data mining, bringing data from multiple sources under a single authority, increases the risk of privacy violations. Privacy preserving data mining provides a means of addressing this issue, particularly if data mining is done in a way that doesn’t disclose information beyond the result. This paper presents a method for privately computing k − nn classification from distributed sources without revealing any information about the sources or their data, other than that revealed by the final classification result.
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