Abstract
To protect sensitive information in mined data, researchers need a way to organize a variety of ongoing work. The Rampart framework categorizes protection approaches and encourages interdisciplinary solutions to the growing variety of privacy problems associated with knowledge discovery from data.
Original language | English |
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Pages | 54-62 |
Number of pages | 9 |
Volume | 49 |
No. | 2 |
Specialist publication | Computer |
DOIs | |
Publication status | Published - Feb 2016 |
Externally published | Yes |
Keywords
- big data
- big data management
- data mining
- game theory
- information privacy
- information security
- privacy
- provenance
- sensitive information
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Xu, L., Jiang, C., Chen, Y., Wang, J., & Ren, Y. (2016). A Framework for Categorizing and Applying Privacy-Preservation Techniques in Big Data Mining. Computer, 49(2), 54-62. https://doi.org/10.1109/MC.2016.43