ON ASSESSING THE DISCLOSURE RISK OF CONTROLLED ADJUSTMENT METHODS FOR STATISTICAL TABULAR DATA

DOI10.1142/S0218488512400314zbMath1320.68074OpenAlexW2005032141MaRDI QIDQ2948291

Jordi Castro

Publication date: 30 September 2015

Published in: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218488512400314

zbMATH Keywords

optimizationlinear programmingquadratic programmingstatistical disclosure controlcontrolled tabular adjustmentdisclosure risk

Mathematics Subject Classification ID

Related Items (3)

Fix-and-relax approaches for controlled tabular adjustment ⋮ Perspective Reformulations of the CTA Problem with L₂ Distances ⋮ A linear optimization-based method for data privacy in statistical tabular data

Cites Work

• Recent advances in optimization techniques for statistical tabular data protection
• Minimum-distance controlled perturbation methods for large-scale tabular data protection
• A CRITIQUE OF THE SENSITIVITY RULES USUALLY EMPLOYED FOR STATISTICAL TABLE PROTECTION

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