A survey on statistical disclosure control and micro-aggregation techniques for secure statistical databases

Software - Practice and Experience

Volumn 40, Issue 12, 2010, Pages 1161-1188

  Fayyoumi, Ebaa ^a   Oommen, B John ^b,c  

^a HASHEMITE UNIVERSITY   (Jordan)

^b CARLETON UNIVERSITY   (Canada)

^c UNIVERSITY OF AGDER   (Norway)

Author keywords

disclosure risk; information loss; micro aggregation problem; micro aggregation techniques; secure statistical databases; statistical disclosure control

Indexed keywords

DISCLOSURE RISK; INFORMATION LOSS; MICRO-AGGREGATION PROBLEM; MICRO-AGGREGATION TECHNIQUES; SECURE STATISTICAL DATABASE; STATISTICAL DISCLOSURE CONTROL;

DATABASE SYSTEMS; SURVEYS;

STATISTICS;

EID: 78249243883     PISSN: 00380644     EISSN: 1097024X     Source Type: Journal    
DOI: 10.1002/spe.992     Document Type: Article

References (138)

1. Date C,. An Introduction to Database Systems. Addison-Wesely: Reading, MA, 2000.
2. Beck L,. A security mechanism for statistical database. ACM Transactions on Database Systems 1980; 5 (3): 316-338.
3. Fernandez E, Summers R, Wood C,. Databases Security and Integrity. Addison-Wesley: Reading, MA, 1980.
4. Adam N, Wortmann J,. Security-control methods for statistical databases: A comparative study. ACM Computing Surveys 1989; 21 (4): 515-556.
5. Aggarwal C, Yu P,. Privacy-preserving Data Mining. Springer: Berlin, 2008.
6. Jonge W,. Compromising statistical databases responding to queries about means. ACM Transactions on Database Systems 1983; 8 (1): 60-80.
7. Mandujano S,. Inference attacks to statistical databases: Data suppression, concealing controls and other security trends. Technical Report, Department of Computer Science, Purdue University, 2001.
8. Schatz J,. Survey of techniques for securing statistical databases. Technical Report, University of California at Davis, 1997.
9. Denning D,. Secure statistical databases with random sample queries. ACM Transactions on Database Systems 1980; 5 (3): 291-315.
10. Muralidhar K, Sarathy R,. Security of random data perturbation methods. ACM Transactions on Database Systems 1999; 24 (4): 487-493.
11. Nordholt E,. Statistical disclosure control from a users' point of view. Technical Report, Statistics Netherlands, 2001.
12. Nin J, Torra V,. Modeling projections in microaggregation. Proceedings of the 12th International Conference on Information Processing and Management of Uncertainty in Knowledge-based System (IPMU), Malaga, Spain, 2008; 138-145.
13. Domingo-Ferrer J,. Microaggregation for Database and Location Privacy, vol. 4032. Springer: Berlin, Heidelberg, 2006; 106-116.
14. Domingo-Ferrer J, Torra V,. A quantitative comparison of disclosure control methods for microdata. Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies, Doyle P, Lane J, Theeuwes J, Zayatz L, (eds). Springer, North-Holland: Berlin, Amsterdam, 2002; 113-134.
15. Domingo-Ferrer J, Torra V,. Fuzzy microaggregation for microdata protection. Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII) 2003; 7 (2): 153-159.
16. Mateo-Sanz J, Sebé F, Domingo-Ferrer J,. Outlier Protection in Continuous Microdata Masking. Springer: Berlin, Spain, Barcelona, 2004; 201-215.
17. Torra V,. Microaggregation for categorical variables: A median based approach. Privacy in Statistical Databases: CASC Project International Workshop, PSD 2004 Proceedings, Domingo-Ferrer J, Torra V, (eds). Springer: Berlin, Spain, Barcelona, 2004; 162-174.
18. Torra V, Domingo-Ferrer J,. Towards fuzzy C-means based microaggregation. Advances in Soft Computing: Soft Methods in Probability, Statistics and Data Analysis, Grzegorzewski P, Hryniewicz O, Gil M, (eds). Physica: Germany, Heidelberg, 2002; 289-294.
19. Torra V, Miyamoto S,. Evaluating fuzzy clustering algorithms for microdata protection. Privacy in Statistical Databases: CASC Project International Workshop, PSD 2004 Proceedings, Domingo-Ferrer J, Torra V, (eds). Springer: Berlin, Spain, Barcelona, 2004; 175-186.
20. Denning D, Denning P,. Data security. ACM Computing Surveys 1979; 11 (3): 227-249.
21. Denning D, Denning P,. The tracker: A threat to statistical database security. ACM Transactions on Database Systems 1979; 4 (1): 76-96.
22. Willenborg L, Waal T,. Elements of Statistical Disclosure Control. Springer: New York, 2001; ILL Number: 2132712
23. Castano S, Fugini M, Martella G, Samarati P,. Database Security. Addison-Wesley: Reading, MA, 1994.
24. Crises G,. An introduction to microdata protection for database privacy. Technical Report, 2004.
25. Kenthapadi K,. DIMACS working group on challenges for cryptographers in health data privacy. Technical Report, 2004.
26. Mas M,. Statistical data protection techniques. Technical Report, Eustat, Euskal Estatistika Erakundea, Instituto Vasco De Estadistica, 2006.
27. Oganian A,. Security and information loss in statistical data protection. PhD Thesis, University URV Catalunya, 2002.
28. Willenborg L, Waal T,. Statistical Disclosure Control in Practice (Lecture Notes in Statistics, vol. 111). Springer: Berlin, 1996.
29. Aggarwal C, Yu P,. Privacy-Preserving Data Mining: Models and Algorithms (Advances in Database Systems). Springer Science and Business Media L.L.C.: Berlin, Heidelberg, 2008.
30. Cuppen M,. Secure data perturbation in statistical disclosure control. PhD Thesis, Statistics Netherlands, 2000.
31. Domingo-Ferrer J, Torra V,. Ordinal, continuous and heterogeneous k-anonymity through microaggregation. Data Mining and Knowledge Discovery 2005; 11 (2): 195-212.
32. Domingo-Ferrer J, Mateo-Sanz J,. Practical data-oriented microaggregation for statistical disclosure control. IEEE Transactions on Knowledge and Data Engineering 2002; 14 (1): 189-201.
33. Sweeney L,. Computational disclosure control for medical microdata: The Datafly system. Record Linkage Techniques. National Academy Press: Washington, DC, 1997; 442-453.
34. Hundepool A, Wetering A, Ramaswamy R, Franconi L, Capobianchi A, Wolf P, Domingo-Ferrer J, Torra V, Brand R, Giessing S,. M-ARGUS Version 4.0 Software and User's Manual, 2004.
35. Reddy B,. Aspects of database security and program security. Technical Report, Kanwal Rekhi School of Information Technology, Indian Institute of Technology-Bombay, 2003.
36. Crises G,. Microdata disclosure risk in database privacy protection. Technical Report, 2004.
37. Domingo-Ferrer J, Mateo-Sanz J,. An empirical comparison of SDC methods for continuous micro-data in terms of information loss and disclosure risk. Joint ECE/Eurostat Work Session on Statistical Data Confidentiality, Conference of European Satisticians, Statistical Commision and Economic Commision for Europe, 2001.
38. Domingo-Ferrer J, Mateo-Sanz J, Torra V,. Comparing SDC methods for microdata on the basis of information loss and disclosure risk. Proceedings of ETK-NTTS'2001, vol. 2. Office for Official Publications of the European Communities: Luxembourg, 2001; 807-825.
39. Giessing S, Hundepool A,. The CASC project: Integrating best practice methods for statistical confidentiality. Technical Report, 2003.
40. Crises G,. Information loss measures for microdata in database privacy protection. Technical Report, 2004.
41. Domingo-Ferrer J, Torra V,. Disclosure control methods and information loss for microdata. Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies. North-Holland: Amsterdam, 2002; 93-112.
42. Mateo-Sanz J, Domingo-Ferrer J, Sebé F,. Probabilistic information loss measures in confidentiality protection of continuous microdata. Data Mining and Knowledge Discovery 2005; 11 (2): 181-193.
43. Sanchez J, Urrutia J, Ripoll E,. Test report on multivariate microaggregation in m-Argus 3.2. Technical Report, CASC PROJECT, Computational Aspects of Statistical Confidentiality, 2003.
44. Crises G,. Trading off information loss and disclosure risk in database privacy protection. Technical Report, 2004.
45. Kim J, Winkler W, Bureau of The Census,. Masking microdata files. Proceedings of the Survey Research Methods Section, American Statistical Association, 1995; 114-119.
46. Sullivan G, Fuller W,. The use of measurement error to avoid disclosure. The Section on Survey Research Methods 1989; 802-807.
47. Sebé F, Domingo-Ferrer J, Mateo-Sanz J, Torra V,. Post-masking optimization of the tradeoff between information loss and disclosure risk in masked microdata sets. Inference Control in Statistical Databases, from Theory to Practice. Springer: London, U.K., 2002; 163-171.
48. Zaslavsky A, Horton N,. Balancing disclosure risk against the loss of nonpublication. Journal of Official Statistics 1998; 14 (4): 411-419.
49. Crises G,. Synthetic microdata generation for database privacy protection. Technical Report, 2004.
50. Dandekar R, Cohen M, Kirkendall N,. Sensitive micro data protection using latin hypercube sampling technique. Inference Control in Statistical Databases, From Theory to Practice. Springer: London, U.K., 2002; 117-125.
51. Domingo-Ferrer J, Mateo-Sanz J, Sebe F,. Information loss in continuous hybrid microdata: Subdomain-level probabilistic measures. Soft Computing for Information Retrieval on the Web: Models and Applications, Studies in Fuzziness, 2006; 287-298.
52. Winkler W,. Re-identification methods for masked microdata. Privacy in Statistical Databases: CASC Project International Workshop, PSD 2004, Domingo-Ferrer J, Torra V, (eds). Springer: Berlin, Spain, Barcelona, 2004; 216-223.
53. Crises G,. Perturbative masking for microdata privacy protection in statistical databases. Technical Report, 2004.
54. Hundepool A, Domingo-Ferrer J, Franconi L, Giessing S, Lenz R, Longhurst J, Nordholt E, Seri G, Wolf P,. Handbook on Statistical Disclosure Control. A CENtre of EXcellence for Statistical Disclosure Control CENEX SDC, 2006.
55. Kooiman P, Willenborg L, Gouweleeuw J,. PRAM: A method for disclosure limitation of microdata. Technical Report, 1998.
56. Domingo-Ferrer J, Mateo-Sanz J,. On resampling for statistical confidentiality in contingency tables. Computers and Mathematics with Applications 1999; 38: 13-32.
57. Dwork C, McSherry F, Nissim K, Smith A,. Calibrating noise to sensitivity in private data analysis. Third Conference on Cryptography-TCC, New York, U.S.A., 2006; 365-384.
58. Dwork C,. Differential privacy. Thirty-third International Colloquium on Automata, Languages and Programming-ICALP 2006, Part II, 1-12.
59. Dwork C,. Differential Privacy: A Survey of Results. TAMC 2008 (Lecture Notes in Computer Science, vol. 4978), Agrawal M, Du D-Z, Duan Z, Li A, (eds). Springer: Berlin, 2008; 1-19.
60. Dwork C, Yekhanin S,. New efficient attacks on statistical disclosure control mechanisms. Advances in Cryptology-CRYPTO 2008, Santa Barbara, CA, U.S.A., 2008.
61. Rubin DB,. Multiple Imputations for Nonresponse in Surveys. Wiley: New York, NY, 1987.
62. Raghunathan TE, Reiter JP, Rubin DR,. Multiple imputation for statistical disclosure limitation. Journal of Official Statistics 2003; 8: 531-544.
63. Reiter JP,. Inference for partially synthetic public use microdata sets. Survey Methodology 2003; 29 (2): 181-188.
64. Reiter JP,. Releasing multiply imputed, synthetic public-use microdata: An illustration and empirical study. Journal of the Royal Statistical Society, A 2005; 168 (1): 185-205.
65. Abowd JM,. How protective are synthetic data? Privacy in Statistical Databases, Domingo-Ferrer J, Yucel V, (eds). Springer: New York, NY, 2008; 239-246.
66. Machanavajjhala A, Kifer D, Abowd J, Gehrke J, Vilhuber L,. Privacy: Theory meets practice on the map.ICDE 2008, 2008.
67. Little RJ, Liu F,. Selective multiple imputation of keys for statistical disclosure control in microdata. American Statistical Association, Proceedings of the Section on Survey Research Methods, Ottawa, Canada, 2002; 2133-2138.
68. Little RJ, Liu F,. Comparison of SMIKe with data-swapping and PRAM for statistical disclosure control of simulated microdata. American Statistical Association, Proceedings of the Section on Survey Research Methods, Ottawa, Canada, 2003.
69. Evfimievski A, Gehrke J, Srikant R,. Limiting privacy breaches in privacy preserving data mining. ACM PODS Conference, Paris, France, 2004; 211-222.
70. Evfimievski A,. Privacy preserving information sharing. PhD Dissertation, Cornell University, 2004.
71. Evfimievski A, Srikant R, Agrawal R, Gehrke J,. Privacy preserving mining of association rules. Association of Computing Machinery, Special Interest Group on Knowledge Discovery and Datamining, Edmonton, Canada, 2002.
72. Crises G,. Non-perturbative methods for microdata privacy in statistical databases. Technical Report, 2004.
73. Panaretos J, Tzyvidis N,. Aspects of estimation procedures at Eurostat with some emphasis on over-space harmonization. HERCMA 2001 Conference, 2001.
74. Baeyens Y, Defays D,. Estimation of variance loss following microaggregation by the individual ranking method. Proceedings of Statistical Data Protection'98. Office for Official Publications of the European Communities: Luxembourg, 1999; 101-108.
75. Mateo-Sanz J, Domingo-Ferrer J,. A method for data-oriented multivariate microaggregation. Proceedings of Statistical Data Protection'98. Office for Official Publications of the European Communities: Luxembourg, 1999; 89-99.
76. Domingo-Ferrer J, Torra V,. Aggregation techniques for statistical confidentiality. Aggregation Operators: New Trends and Applications. Physica-Verlag GmbH: Germany, Heidelberg, 2002; 260-271.
77. Crises G,. Microaggregation for privacy protection in statistical databases. Technical Report, 2004.
78. Domingo-Ferrer J,. Statistical disclosure control in Catalonia and the CRISES group. Technical Report, 1999.
79. Hansen S, Mukherjee S,. A polynomial algorithm for univariate optimal microaggregation. IEEE Transactions on Knowledge and Data Engineering 2003; 15 (4): 1043-1044.
80. Laszlo M, Mukherjee S,. Minimum spanning tree partitioning algorithm for microaggregation. IEEE Transactions on Knowledge and Data Engineering 2005; 17 (7): 902-911.
81. Domingo-Ferrer J, Solanas A, Martínez-Balleste A,. Privacy in statistical databases: k-Anonymity through microaggregation. Proceedings of IEEE Granular Computing 2006, Atlanta, GA, U.S.A., 2006; 774-777.
82. Defays D,. Protecting microdata by microaggregation: The experience in Eurostat. Questiio 1997; 21: 221-231.
83. Defays D, Anwar M,. Masking micro-data using micro-aggregation. Journal of Official Statistics 1998; 14 (4): 449-461.
84. Mateo-Sanz J, Domingo-Ferrer J,. A comparative study of microaggregation methods. Questiio 1998; 22 (3): 511-526.
85. Anwar N,. Micro-aggregation-The small aggregates method. Technical Report, Eurostat, Luxembourg, 1993.
86. Defays D, Anwar N,. Micro-aggregation: A generic method. Proceedings of the 2nd International Symposium on Statistical Confidentiality. Office for Official Publications of the European Communities: Luxembourg, 1995; 69-78.
87. Defays D, Nanopoulos P,. Panels of enterprises and confidentiality: The small aggregates method. Proceedings of 92 Symposium on Design and Analysis of Longitudinal Surveys, Statistics Canada, Ottawa, 1993; 195-204.
88. Domingo-Ferrer J, Mateo-Sanz J, Oganian A, Torra V, Torres A,. On the security of microaggregation with individual ranking: Analytical attacks. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems 2002; 10 (5): 477-491.
89. Li Y, Zhu S, Wang L, Jajodia S,. A privacy-enhanced microaggregation method. FoIKS '02: Proceedings of the Second International Symposium on Foundations of Information and Knowledge Systems. Springer: London, U.K., 2002; 148-159.
90. Solanas A, Martínez-Ballesté A,. V-MDAV: A multivariate microaggregation with variable group size. Seventh COMPSTAT Symposium of the IASC, Rome, 2006.
91. Ward J,. Hierarchical grouping to optimize an objective function. Journal of American Statistical Association 1963; 58: 236-245.
92. Fayyoumi E, Oommen BJ,. On optimizing the k-ward micro-aggregation technique for secure statistical databases. Eleventh Australasian Conference on Information Security and Privacy Proceeding, Australia, Melbourne, 2006; 324-335.
93. Sande G,. Methods for data directed micro-aggregation in one dimension. Proceedings of NTTS and ETK: New Techniques and Technologies for Statistics and Exchange for Technology and Know-how, Crete, June 18-22.
94. Sande G,. Exact and approximate methods for data directed microaggregation in one or more dimensions. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems 2002; 10 (5): 459-476.
95. Oganian A, Domingo-Ferrer J,. On the complexity of optimal microaggregation for statistical disclosure control. Statistical Journal of the United Nations Economic Commission for Europe 2001; 18 (4): 345-354.
96. Solanas A, Martínez-Ballesté A, Domingo-Ferrer J, Mateo-Sanz J,. A 2d-tree-based blocking method for microaggregating very large data sets. The First International Conference on Availability, Reliability and Security. The International Dependability Conference Bridging Theory and Practice, Vienna, Austria, 2006.
97. El-Hamdouchi A, Willet P,. Hierarchic document clustering using Ward's method. Proceedings of the Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Pisa, Italy, 1986; 149-156.
98. Jain A, Murty M, Flynn P,. Data clustering: A review. ACM Computing Surveys 1999; 31 (3): 264-323.
99. Domingo-Ferrer J,. Microaggregation: Achieving k-anonymity with quasi-optimal data quality. Proceedings of Q2006: European Conference on Quality in Survey Statistics, 2006.
100. Domingo-Ferrer J, Sebe F, Solanas A,. A polynomial-time approximation to optimal multivariate microaggregation. Computers and Mathematics with Applications 2008; 55: 714-732.
101. Domingo-Ferrer J, Sebé F,. Optimal multivariate 2-microaggregation for microdata protection: A 2-approximation. Privacy Statistical Databases, Italy, Rome, 2006; 129-138.
102. Martinez-Balleste A, Solanas A, Domingo-Ferrer J, Mateo-Sanz J,. A genetic approach to multivariate microaggregation for database privacy. ICDE Workshops, Istanbul, Turkey, 2007; 180-185.
103. Fayyoumi E, Oommen BJ,. A fixed structure learning automaton micro-aggregation technique for secure statistical databases. Privacy Statistical Databases, Italy, Rome, 2006; 114-128.
104. Fayyoumi E, Oommen BJ,. Achieving microaggregation for secure statistical databases using fixed-structure partitioning-based learning automata. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 2009; 39 (5): 1192-1205.
105. Oommen B, Fayyoumi E,. A novel method for micro-aggregation in secure statistical databases using association and interaction. Information and Communications Security, 9th International Conference on Information and Communications Security (Lecture Notes in Computer Science, vol. 4861). Springer: Berlin, 2007; 126-140.
106. Oommen BJ, Fayyoumi E,. On utilizing association and interaction concepts for enhancing microaggregation in secure statistical databases. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 2010; 40: 198-207.
107. Oommen BJ, Fayyoumi E,. An AI-based causal strategy for securing statistical databases using micro-aggregation. Twenty-first Australasian Joint Conference on Artificial Intelligence, vol. 5360. Springer: Berlin, Heidelberg, 2008; 423-434.
108. Oommen BJ, Fayyoumi E,. Enhancing micro-aggregation technique by utilizing dependence-based information in secure statistical databases. Information Security and Privacy, 13th Australasian Conference on Information Security and Privacy Proceeding (Lecture Notes in Computer Science, vol. 5107). Springer: Berlin, 2008; 404-418.
109. Domingo-Ferrer J, Torra V,. Extending microaggregation procedures using defuzzification methods for categorical variables. IEEE Intelligent Systems'2002, Varna, Bulgaria, 2002; 44-49.
110. Domingo-Ferrer J, Torra V,. Median-based aggregation operators for prototype construction in ordinal scales. International Journal of Intelligent Systems 2003; 18 (6): 633-655.
111. Feige E, Watts H,. Protection of privacy through microaggregation. Data bases, Computers and the Social Sciences. Wiley: New York, 1970; 261-272.
112. Domingo-Ferrer J,. Microaggregation for database and location privacy. Next Generation Information Technologies and Systems-NGITS'2006, 2006; 106-116.
113. Domingo-Ferrer J, Torra V,. On the connections between statistical disclosure control for microdata and some artificial intelligence tools. Information Sciences 2003; 151: 153-170.
114. Mateo J, Domingo-Ferrer J, Sebé F, Martinez-Balleste A, Torres A, Macia N,. New microaggregation algorithms software documentation and related papers. Technical Report, CASC PROJECT, Computational Aspects of Statistical Confidentiality, 2002.
115. Sanchez J, Urrutia J, Ripoll E,. Trade-off between disclosure risk and information loss using multivariate microaggregation: A case study on business data. Privacy in Statistical Databases: CASC Project International Workshop, PSD 2004 Proceedings, Domingo-Ferrer J, Torra V, (eds). Springer: Spain, Barcelona, 2004; 307-322.
116. Brand R, Domingo-Ferrer J, Mateo-Sanz J,. Reference data sets to test and compare SDC methods for protection of numerical microdata. Technical Report, CASC PROJECT, Computational Aspects of Statistical Confidentiality, 2002; 469-480.
117. Wende T,. Different Grades of Statistical Disclosure Control Correlated with German Statistics Law. Springer: Berlin, Spain, Barcelona, 2004; 336-342.
118. Bechet L, Loosveldt P,. Development of micro-aggregation software. Technical Report, Ariane II, 275 route d'Arlon, L-8011 Strassen, Luxembourg, 2000.
119. Oganian A, Karr F,. Combinations of SDC methods for microdata protection. Privacy Statistical Databases, Italy, Rome, 2006; 102-113.
120. Valls A, Torra V, Domingo-Ferrer J,. Aggregation methods to evaluate multiple protected versions of the same confidential data set. Soft Methods in Probability, Statistics and Data Analysis (Warsaw, 2002), Grzegorzewski P, Hryniewicz O, Gil M, (eds). Physica-Verlag: Germany, Heidelberg, 2002; 355-362.
121. Brucker P,. On the complexity of clustering problems. Optimization and Operations Research, Hehn R, Korte B, Oettli W, (eds). Springer: Berlin, 1977; 45-54.
122. Tasoulis D, Vrahatis M,. Unsupervised clustering on dynamic databases. Pattern Recognition Letters 2005; 26: 2116-2127.
123. Vrahatis M, Boutsinas B, Alevizos P, Pavlides G,. The new k-windows algorithm for improving the k-means clustering algorithm. Journal of Complexity 2002; 18: 375-391.
124. Yancey W, Winkler W, Creecy R,. Disclosure risk assessment in perturbative microdata protection. Inference Control in Statistical Databases, From Theory to Practice. Springer: London, U.K., 2002; 135-152.
125. Domingo-Ferrer J, Sebé F, Castellà-Roca J,. On the Security of Noise Addition for Privacy in Statistical Databases. Springer: Berlin, Spain, Barcelona, 2004; 149-161.
126. Dwork C, McSherry F, Talwar K,. The price of privacy and the limits of LP decoding. STOC2007, San Diego, CA, 2007; 85-94.
127. Wilson R, Rosen P,. Protecting data through perturbation techniques: The impact on knowledge discovery in databases. Journal of Database Management 2003; 14 (2): 14-26.
128. Gouweleeuw J, Kooiman P, Willenborg L, Wolf P,. Post randomization for statistical disclosure control: Theory and implementation. Technical Report, 1997.
129. Wolf P, Gouweleeuw J, Kooiman P, Willenborg L,. Reflections on PRAM. Technical Report, 1997.
130. Torra V, Abowd J, Domingo-Ferrer J,. Using mahalanobis distance-based record linkage for disclosure risk assessment. Privacy in Statistical Databases-PSD 2006 2006; 233-242.
131. Elliot M,. Integrating file and record level disclosure risk assessment. Inference Control in Statistical Databases, From Theory to Practice. Springer: London, U.K., 2002; 126-134.
132. Hundepool A, Wetering L, Gemerden L, Wessels A, Fischetti M, Salazar J, Caprara A,. t-ARGUS User's Manual, 1998.
133. Dwork C, McSherry F, Talwar K,. Differentially private marginals release with mutual consistency and error independent sample size. UNECE Worksession on Statistical Data Confidentiality, Manchester, U.K., 2007.
134. Felso F, Theeuwes J, Wagner G,. Disclosure limitation methods in use: Results of a survey. Confidentiality, Disclosure and Data Access. North-Holland: Amsterdam, 2001; 17-42.
135. Moore R,. Controlled data-swapping techniques for masking public use microdata sets. Technical Report, Statistical Research Division Report Series, Washington, DC, 1996.
136. Brand R,. Microdata Protection through noise addition. Inference Control in Statistical Databases, From Theory to Practice. Springer: London, U.K., 2002; 97-116.
137. Crises G,. Additive noise for microdata privacy protection in statistical databases. Technical Report, 2004.
138. Fuller W,. Masking procedures for microdata disclosure limitation. Journal of Official Statistics 1993; 9 (2): 383-406.