BOOK-CHAPTER

Secure Multiparty Computation for Privacy Preserving Data Mining

Abstract

The increasing use of data-mining tools in both the public and private sectors raises concerns regarding the potentially sensitive nature of much of the data being mined. The utility to be gained from widespread data mining seems to come into direct conflict with an individual's need and right to privacy. Privacy-preserving data-mining solutions achieve the somewhat paradoxical property of enabling a data-mining algorithm to use data without ever actually seeing it. Thus, the benefits of data mining can be enjoyed without compromising the privacy of concerned individuals. Request access from your librarian to read this chapter's full text.

Keywords:
Secure multi-party computation Computer science Computer security Internet privacy Computation Cryptography Algorithm

Metrics

32
Cited By
2.63
FWCI (Field Weighted Citation Impact)
39
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cryptography and Data Security
Physical Sciences →  Computer Science →  Artificial Intelligence
Privacy-Preserving Technologies in Data
Physical Sciences →  Computer Science →  Artificial Intelligence
Complexity and Algorithms in Graphs
Physical Sciences →  Computer Science →  Computational Theory and Mathematics

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