Inference Control in Statistical Databases, From Theory to Practice

Advances in Inference Control in Statistical Databases: An Overview.- Advances in Inference Control in Statistical Databases: An Overview.- Tabular Data Protection.- Cell Suppression: Experience and Theory.- Bounds on Entries in 3-Dimensional Contingency Tables Subject to Given Marginal Totals.- Extending Cell Suppression to Protect Tabular Data against Several Attackers.- Network Flows Heuristics for Complementary Cell Suppression: An Empirical Evaluation and Extensions.- HiTaS: A Heuristic Approach to Cell Suppression in Hierarchical Tables.- Microdata Protection.- Model Based Disclosure Protection.- Microdata Protection through Noise Addition.- Sensitive Micro Data Protection Using Latin Hypercube Sampling Technique.- Integrating File and Record Level Disclosure Risk Assessment.- Disclosure Risk Assessment in Perturbative Microdata Protection.- LHS-Based Hybrid Microdata vs Rank Swapping and Microaggregation for Numeric Microdata Protection.- Post-Masking Optimization of the Tradeoff between Information Loss and Disclosure Risk in Masked Microdata Sets.- Software and User Case Studies.- The CASC Project.- Tools and Strategies to Protect Multiple Tables with the GHQUAR Cell Suppression Engine.- SDC in the 2000 U.S. Decennial Census.- Applications of Statistical Disclosure Control at Statistics Netherlands.- Empirical Evidences on Protecting Population Uniqueness at Idescat.