k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Anonymizing sequential releases
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Anatomy: simple and effective privacy preservation
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Towards a Privacy Diagnosis Centre: Measuring k-Anonymity
CSA '08 Proceedings of the International Symposium on Computer Science and its Applications
| Hi-index | 0.00 |
The Internet and the World Wide Web democratized the means to publish and share corporate and personal data. Many anecdotes occurred over the last decades that well illustrate the danger for privacy and confidentiality. The advent of Cloud computing infrastructures is likely, if successful, to further encourage this trend. The analysis, diagnosis and prevention of privacy risk within a Cloud computing infrastructure are therefore important services to provide to users. In recent years, several algorithms such as K-anonymity, L-diversity and Anatomy, have been proposed to address the issue of data anonymization and diversification. They transform original data sets into modified data sets ensuring some privacy while minimizing the information loss incurred during the transformation. Shared and published data can remain meaningful without jeopardizing privacy. We propose an integrated collection of privacy management services together with an interface to orchestrate their execution and assess their evaluation. The system consists of Web services and Cloud architecture. Cloud users can explore and apply privacy management services as Cloud services. This proposal is a first but significant step towards the general concept of a Cloud of data services and data transformation processes for data privacy, anonymity, security, quality, mining, management, publishing and sharing of data.