k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A three-dimensional conceptual framework for database privacy
SDM'07 Proceedings of the 4th VLDB conference on Secure data management
Capturing P3P semantics using an enforceable lattice-based structure
Proceedings of the 4th International Workshop on Privacy and Anonymity in the Information Society
Privacy-aware spam detection in social bookmarking systems
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Quantifying privacy violations
SDM'11 Proceedings of the 8th VLDB international conference on Secure data management
Decentralised privacy preservation in social networks
International Journal of Business Information Systems
"Valuing" privacy while exposing data utility
BNCOD'10 Proceedings of the 27th British national conference on Data Security and Security Data
Semantic metadata management in web 2.0
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Redeem with privacy (RWP): privacy protecting framework for geo-social commerce
Proceedings of the 12th ACM workshop on Workshop on privacy in the electronic society
A classification of location privacy attacks and approaches
Personal and Ubiquitous Computing
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Privacy has become increasingly important to the database community which is reflected by a noteworthy increase in research papers appearing in the literature. While researchers often assume that their definition of "privacy" is universally held by all readers, this is rarely the case; so many papers addressing key challenges in this domain have actually produced results that do not consider the same problem, even when using similar vocabularies. This paper provides an explicit definition of data privacy suitable for ongoing work in data repositories such as a DBMS or for data mining. The work contributes by briefly providing the larger context for the way privacy is defined legally and legislatively but primarily provides a taxonomy capable of thinking of data privacy technologically. We then demonstrate the taxonomy's utility by illustrating how this perspective makes it possible to understand the important contribution made by researchers to the issue of privacy. The conclusion of this paper is that privacy is indeed multifaceted so no single current research effort adequately addresses the true breadth of the issues necessary to fully understand the scope of this important issue.