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Integrating File and Record Level Disclosure Risk Assessment

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Inference Control in Statistical Databases

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2316))

Abstract

This paper examines two methods of record-level disclosure risk assessment for microdata. The first uses an extension of the Special Uniques Identification method [7] combined with data mining techniques and the second uses Data Intrusion Simulation methodology [4],[14] at the record level. Some numerical studies are presented showing the value of these two methods and proposals for integrating them with file level measures in risk driven file construction system are presented.

The work described in this paper was supported by the UK Economic and Social Research Council, grant number R000 22 2852.

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References

  1. Bethlehem, J.G., Keller, W.J., and Pannekoek, J. Disclosure control of microdata, Journal of the American Statistical Association Vol. 85, 38–45, 1990.

    Article  Google Scholar 

  2. Dalenius, T. Finding a Needle in a Haystack. Journal of Official Statistics Vol.2, No.3, 329–336, 1986.

    Google Scholar 

  3. Efron, B. Bootstrap methods: Another Look at the Jack-knife. Annals of Statistics, Vol. 7. 1–26, 1979.

    Article  MATH  MathSciNet  Google Scholar 

  4. Elliot, M.J. DIS: “A new approach to the measurement of statistical disclosure risk.” International Journal of Risk Management 2(4) (2000): 39–48.

    Article  Google Scholar 

  5. Elliot, M.J. “Data intrusion Simulation: Advances and a vision for the future of disclosure control.” Paper presented to the 2nd UNECE work session on statistical data confidentiality; Skopje March 2001.

    Google Scholar 

  6. Elliot, M.J. and Dale, A. “Scenarios of Attack: The data intruder’s perspective on statistical disclosure risk.” Netherlands Official Statistics. Spring 1999.

    Google Scholar 

  7. Elliot, M.J., and Manning, A. “The Identification of Special Uniques”. To appear in Proceedings Of GSS Methodology Conference. London. June 2001.

    Google Scholar 

  8. Elliot, M.J. and Manning, A. Statistical Disclosure Control and Data Mining. Proposal document to Economic and Social research Council under grant number (grant number R000 22 2852).

    Google Scholar 

  9. Elliot, M.J., Skinner, C.J., and Dale, A. “Special Uniques, Random Uniques and Sticky Populations: Some Counterintuitive Effects of Geographical Detail on Disclosure Risk”. Research in Official Statistics; 1(2), 53–68, 1998.

    Google Scholar 

  10. Fienberg, S.E. and Makov, U.E., “Confidentiality Uniqueness and Disclosure Limitation for Categorical Data”, Journal of Official Statistics 14(4), pp. 361–372, 1998.

    Google Scholar 

  11. Greenberg, B.V. and Zayatz, L.V. Strategies for Measuring Risk in Public Use Microdata Files. Statistica Neerlandica, 46, 33–48, 1992.

    Article  Google Scholar 

  12. Muller, W., Blien, U., and Wirth, H. “Disclosure risks of anonymous individual data.” Paper presented at the 1st International Seminar for Statistical Disclosure. Dublin, 1992.

    Google Scholar 

  13. Samuels, S.M. “A Bayesian, Species-Sampling-Inspired Approach to the Uniques Problem in Microdata Disclosure Risk Assessment.” Journal of Official Statistics. 14(4) 373–383, 1998.

    MathSciNet  Google Scholar 

  14. Skinner, C.J. and Elliot, M.J. ‘A Measure of Disclosure Risk for Microdata’. CCSR occasional paper 23, 2001.

    Google Scholar 

  15. Skinner, C.J. and Holmes, D. J., “Estimating the Re-identification Risk per Record”, Journal of Official Statistics 14(4). pp. 361–372, 1998.

    Google Scholar 

  16. Tranmer, M., Fieldhouse E., Elliot, M.J., Dale A., and Brown, M. Proposals for Small Area Microdata. Accepted subject to revisions Journal of the Royal Statistical Society, Series A.

    Google Scholar 

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Elliot, M. (2002). Integrating File and Record Level Disclosure Risk Assessment. In: Domingo-Ferrer, J. (eds) Inference Control in Statistical Databases. Lecture Notes in Computer Science, vol 2316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47804-3_10

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  • DOI: https://doi.org/10.1007/3-540-47804-3_10

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  • Print ISBN: 978-3-540-43614-0

  • Online ISBN: 978-3-540-47804-1

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