On the comparison of microdata disclosure control algorithms
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
POkA: identifying pareto-optimal k-anonymous nodes in a domain hierarchy lattice
Proceedings of the 18th ACM conference on Information and knowledge management
Optimal random perturbation at multiple privacy levels
Proceedings of the VLDB Endowment
Privacy Preserving Categorical Data Analysis with Unknown Distortion Parameters
Transactions on Data Privacy
On the identification of property based generalizations in microdata anonymization
DBSec'10 Proceedings of the 24th annual IFIP WG 11.3 working conference on Data and applications security and privacy
Small domain randomization: same privacy, more utility
Proceedings of the VLDB Endowment
Non-black-box computation of linear regression protocols with malicious adversaries
ISPEC'11 Proceedings of the 7th international conference on Information security practice and experience
Application and analysis of multidimensional negative surveys in participatory sensing applications
Pervasive and Mobile Computing
Journal of Computer Security
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The randomized response (RR) technique is a promising technique to disguise private categorical data in Privacy-Preserving Data Mining (PPDM). Although a number of RR-based methods have been proposed for various data mining computations, no study has systematically compared them to find optimal RR schemes. The difficulty of comparison lies in the fact that to compare two PPDM schemes, one needs to consider two conflicting metrics: privacy and utility. An optimal scheme based on one metric is usually the worst based on the other metric. In this paper, we first describe a method to quantify privacy and utility. We formulate the quantification as estimate problems, and use estimate theories to derive quantification. We then use an evolutionary multi-objective optimization method to find optimal disguise matrices for the randomized response technique. The experimental results have shown that our scheme has a much better performance than the existing RR schemes.