Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
Security of random data perturbation methods
ACM Transactions on Database Systems (TODS)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
On the design and quantification of privacy preserving data mining algorithms
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Inference in MLS Database Systems
IEEE Transactions on Knowledge and Data Engineering
Wizard: A Database Inference Analysis and Detection System
IEEE Transactions on Knowledge and Data Engineering
Secure Databases: Constraints, Inference Channels, and Monitoring Disclosures
IEEE Transactions on Knowledge and Data Engineering
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Cardinality-Based Inference Control in Sum-Only Data Cubes
ESORICS '02 Proceedings of the 7th European Symposium on Research in Computer Security
Limiting privacy breaches in privacy preserving data mining
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Achieving k-anonymity privacy protection using generalization and suppression
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Privacy preserving mining of association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Catalytic Inference Analysis: Detecting Inference Threats due to Knowledge Discovery
SP '97 Proceedings of the 1997 IEEE Symposium on Security and Privacy
A formal analysis of information disclosure in data exchange
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
When do data mining results violate privacy?
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A Framework for High-Accuracy Privacy-Preserving Mining
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Data Privacy through Optimal k-Anonymization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
On the complexity of optimal K-anonymity
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Incognito: efficient full-domain K-anonymity
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Checking for k-anonymity violation by views
VLDB '05 Proceedings of the 31st international conference on Very large data bases
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Privacy in database publishing
ICDT'05 Proceedings of the 10th international conference on Database Theory
Authorization views and conditional query containment
ICDT'05 Proceedings of the 10th international conference on Database Theory
Toward privacy in public databases
TCC'05 Proceedings of the Second international conference on Theory of Cryptography
Controlling inference: avoiding p-level reduction during analysis
ACSW '07 Proceedings of the fifth Australasian symposium on ACSW frontiers - Volume 68
How Anonymous Is k-Anonymous? Look at Your Quasi-ID
SDM '08 Proceedings of the 5th VLDB workshop on Secure Data Management
An Anonymity Model Achievable Via Microaggregation
SDM '08 Proceedings of the 5th VLDB workshop on Secure Data Management
Evaluating privacy threats in released database views by symmetric indistinguishability
Journal of Computer Security - Selected papers from the Third and Fourth Secure Data Management (SDM) workshops
Publishing naive Bayesian classifiers: privacy without accuracy loss
Proceedings of the VLDB Endowment
A composite privacy protection model
IWSEC'07 Proceedings of the Security 2nd international conference on Advances in information and computer security
A privacy policy conflict detection method for multi-owner privacy data protection
Electronic Commerce Research
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Uncertainty and indistinguishability are two independent aspects of privacy. Uncertainty refers to the property that the attacker cannot tell which private value, among a group of values, an individual actually has, and indistinguishability refers to the property that the attacker cannot see the difference among a group of individuals. While uncertainty has been well studied and applied to many scenarios, to date, the only effort in providing indistinguishability has been the well-known notion of k-anonymity. However, k-anonymity only applies to anonymized tables. This paper defines indistinguishability for general situations based on the symmetry among the possible private values associated with individuals. The paper then discusses computational complexities of and provides practical algorithms for checking whether a set of database views provides enough indistinguishability.