Data Mining - Analysis White Papers
Privacy-Preserving Data Mining on Data Grids in the Presence of Malicious Participants
Overview Data privacy is a major threat to the widespread deployment of data grids in domains such as health care and finance. The paper proposes a novel technique for obtaining knowledge - by way of a data mining model - from a data grid, while ensuring that the privacy is cryptographically secure. To the best of one's knowledge, all previous approaches for solving this problem fail in the presence of malicious participants. This paper presents an algorithm which, in addition to being secure against malicious members, is asynchronous, involves no global communication patterns, and dynamically adjusts to new data or newly added resources. As far as one knows, this is the first privacy-preserving data mining algorithm to possess these features in the presence of malicious participants.
| Publisher | Israel Institute of Technology | File Format | |
|---|---|---|---|
| Date Published | June 2004 | ||
| Format | White Papers | ||
| Topics | |||
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