PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
A formal analysis of information disclosure in data exchange
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
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
Personalized privacy preservation
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
(α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
L-diversity: Privacy beyond k-anonymity
ACM Transactions on Knowledge Discovery from Data (TKDD)
Information disclosure under realistic assumptions: privacy versus optimality
Proceedings of the 14th ACM conference on Computer and communications security
Minimality attack in privacy preserving data publishing
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Exclusive Strategy for Generalization Algorithms in Micro-data Disclosure
Proceeedings of the 22nd annual IFIP WG 11.3 working conference on Data and Applications Security
Privacy in database publishing
ICDT'05 Proceedings of the 10th international conference on Database Theory
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
Versatile publishing for privacy preservation
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy streamliner: a two-stage approach to improving algorithm efficiency
Proceedings of the second ACM conference on Data and Application Security and Privacy
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In disclosing micro-data with sensitive attributes, the goal is usually two fold. First, the data utility of disclosed data should be maximized for analysis purposes. Second, the private information contained in such data must be limited to an acceptable level. Recent studies show that adversarial inferences using knowledge about a disclosure algorithm can usually render the algorithm unsafe. In this paper, we show that an existing unsafe algorithm can be transformed into a large family of distinct safe algorithms, namely, k-jump algorithms. We prove that the data utility of different k-jump algorithms is generally incomparable. Therefore, a secret choice can be made among all k-jump algorithms to eliminate adversarial inferences while improving the data utility of disclosed micro-data.