Disclosure control of business microdata: A density-based approach

International Statistical Review

Volumn 77, Issue 2, 2009, Pages 196-211

  Ichim, Daniela ^a  

^a ITALIAN NATIONAL INSTITUTE OF STATISTICS   (Italy)

Author keywords

Business microdata; Local outlier factor; Microdata files for research purposes; Risk of disclosure; Selective masking; Statistical disclosure control

Indexed keywords

EID: 77349109070     PISSN: 03067734     EISSN: 17515823     Source Type: Journal    
DOI: 10.1111/j.1751-5823.2009.00079.x     Document Type: Article

References (32)

1. Bacher, J., Brand, R. & Bender, S. (2002). Re-identifying register data by survey data using cluster analysis: an empirical study. Internat. J. Uncertain. Fuzziness and Knowledge-Based Systems, 10(5), 589-607.
2. Bezzi, M. (2007). An entropy-based method for measuring anonimity. In Proceedings of the IEEE/CreateNet SECOVAL Workshop on the Value of Security through Collaboration, Nice, France, September.
3. Brand, R. (2002). Microdata protection through noise addition. In Inference Control in Statistical Databases. Lecture Notes in Computer Science 2316, Ed. J. Domingo-Ferrer, pp. 97-116. Berlin: Springer-Verlag.
4. Breunig, M., Kriegel, H., Ng, R. T. & Sander, J. (2000). LOF: Identifying density-based local outliers. In ACM SIGMOD International Conference on Management of Data, Dallas, TX, pp. 93-104.
5. Cox, L.H. (1994). Matrix masking methods for disclosure limitation in microdata. Surv. Methodol., 20(2), 165- 169.
6. Cox, L.H. (1995). Protecting confidentiality in business surveys. In Business Survey Methods, Eds. Cox, B.G., Binder, D.A., Chinnappa, B.N., Christianson, A., Colledge, M.J. and Kott, P.S., pp. 443-476. New York: Wiley.
7. Dalenius, T. (1977). Towards a methodology for statistical disclosure control. Stat. Tidskr., 85, 429-444.
8. Defays, D. & Anwar, M.N. (1998). Masking microdata using micro-aggregation. J. Official Statist., 14(4), 449-461.
9. Domingo-Ferrer, J. & Torra, V. (2003). Disclosure risk assessment in statistical microdata protection via advanced record linkage. Statist. Comput., 13(4), 343-354.
10. Domingo-Ferrer, J., Torra, V., Mateo-Sanz, J. M. & Sebé, F. (2005). Empirical disclosure risk assessment of the IPSO synthetic data generators. In Monographs of Official Statistics-Work Session on Statistical Data Confidentiality, Ed. Eurostat, pp. 227-238. Luxembourg: European Commission.
11. Duncan, G.T. & Pearson, R.W. (1991). Enhancing access to microdata while protecting confidentiality: Prospects for the future. Statist. Sci., 6(3), 219-239.
12. Elamir, E. & Skinner, C. (2006). Record level measures of disclosure risk for survey microdata. J. Official Statist., 22(3), 525-539.
13. European Commission. (2004). Innovation in Europe. Results for the EU, Iceland and Norway. Theme 9 Science and Technology. Luxembourg: European Commission. http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=KS-59-04-257. Accessed: 3-06-09.
14. Fellegi, I.P. & Sunter, A.B. (1969). A theory for record linkage. J. Amer. Stat. Assoc., 64(328), 1183-1210.
15. Franconi, L. & Polettini, S. (2004). Individual risk estimation in -ARGUS: A review. In Privacy in Statistical Databases. Lecture Notes in Computer Science 3050, Eds. J. Domingo-Ferrer and V. Torra, pp. 262-272. New York: Springer-Verlag.
16. ISTAT. (2004). Statistiche Sull'innovazione delle Imprese. Anni 1998-2000. Informazioni n. 12.Rome:ISTAT.
17. Lambert, D. (1993). Measures of disclosure risk and harm. J. Official Statist., 9(2), 313-333.
18. Little, R. (1993). Statistical analysis of masked data. J. Official Statist., 9(2), 407-426.
19. Machanavajjhala, A., Gehrke J., Kifer, D. & Venkitasubramaniam, M.,(2006). RMTMI.-1.lscript-diversity: Privacy beyond k-anonimity. In Proceedings of the International Conference on Data Engineering (ICDE).
20. Mateo-Sanz, J.M., Sebé, F. & Domingo-Ferrer, J. (2004). Outlier protection in continuous microdata masking. In Privacy in Statistical Databases. Lecture Notes in Computer Science 3050, Eds. J. Domingo-Ferrer and V. Torra, pp. 201-215. New York: Springer-Verlag.
21. Mera, R. (1997). Matrix masking methods which preserve moments. In Proceedings of the Section of Survey Research Methods of the American Statistical Association, pp. 445-450.
22. Moore, R.A. (1996). Controlled data-swapping techniques for masking public use microdata sets. Statistical Research Division Report Series, RR96-04, U.S. Bureau of the Census. Washington DC.
23. Paass, G. (1988). Disclosure risk and disclosure avoidance for microdata. J. Bus. Econom. Statist., 6, 487-500.
24. Polettini, S. (2003). Some remarks on the individual risk methodology. In Proceedings of the Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality, pp. 299-311.
25. Polettini, S., Franconi, L. & Stander, J. (2002). Model based dislcosure protection. In Inference Control in Statistical Databases. Lecture Notes in Computer Science 2316, Ed. J. Domingo-Ferrer, pp. 83-96. Berlin: Springer-Verlag. Rousseeuw, P.J. & Leroy, A.M. (1985). Robust Regression and Outlier Detection.NewYork:Wiley.
26. Ting, D., Fienberg, S.E. & Trottini, M. (2008). Random orthogonal matrix masking for microdata release. Internat. J. Inform. Comput. Secur., 2(1), 86-105.
27. Torra, V. & Domingo-Ferrer, J. (2003). Record linkage methods for multidatabase data mining. In Information Fusion in Data Mining, Ed. V. Torra, pp. 101-132. Berlin: Springer-Verlag.
28. Truta, T.M., Fotouhi, F. & Barth-Jones, D. (2006). Global disclosure risk for microdata with continuous attributes. In Privacy and Technologies of Identity, Eds. Strandburg, K.J. and Raicu, pp. 350-363. New York: D.S. Springer.
29. Sweeny, L. (2002). k-anonimity: A model for protecting privacy. Internat. J. Uncertain. Fuzziness Knowledge-Based Systems, 10(5), 557-570.
30. Willenborg, L. & De Waal, T. (2001). Elements of Statistical Disclosure Control. Lecture Notes in Statistics 155.New York: Springer.
31. Winkler, W. (2004). Re-identification methods for masked microdata. In Privacy in Statistical Databases. Lecture Notes in Computer Science 3050, Eds. J. Domingo-Ferrer and V. Torra, pp. 216-230. Berlin: Springer-Verlag.
32. Zeileis, A., Kleiber, C., Kramer, W. & Hornik, K. (2003). Testing and dating of structural changes in practice. Comput. Statist. Data Anal., 44, 109-123.