An Approach for Privacy Preserving in Association Rule Mining Using Data Restriction

Provided by: International Journal of Engineering and Science Invention (IJESI)
Topic: Data Management
Format: PDF
The sharing of data or mined association rules can bring a lot of advantages for research, marketing, medical analysis and business partnerships; however, large repositories of data contain private data and sensitive rules that must be protected before released. The challenge is protection private data and sensitive rules contained in the source database, while non-sensitive rules can still be mined normally. To address this challenging problem, different sanitization methods were projected in literature. The authors discuss different data restriction methods from sanitization process.

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