Minimizing Disclosure Risk in HHS Open Data Initiatives. References


Alexander, J. Trent, Michael Davern, and Betsey Stevenson. “Inaccurate Age and Sex Data in the Census PUMS Files: Evidence and Implications.” Public Opinion Quarterly, vol. 74, no. 3, Fall 2010, pp. 551-569.

Barth-Jones, Daniel C. “The ‘Re-identification of Governor William Weld’s Medical Information: A Critical Re-examination of Health Data Identification Risks and Privacy Protections, Then and Now.” Working paper. New York: Columbia University, 2012.

Benitez K. and B. Malin. “Evaluating Deidentification Risks with Respect to the HIPAA Privacy Rule.” Journal of the American Medical Informatics Association, vol. 17, 2010, pp. 169–177.

Borton, J.M., A. T-C. Yu, A.M. Crego, A.C. Singh, M.E. Davern, and E.Hair. “Data Entrepreneurs’ Synthetic PUF: A Working PUF as an Alternative to Traditional Synthetic and Non-synthetic PUFs.” Proceedings of the Joint Statistical Meetings. Alexandria: American Statistical Association, 2013.

Cavoukian, Ann, and Daniel Castro. “Big Data and Innovation, Setting the Record Straight: De-identification Does Work.” Toronto, Ontario, Canada: Office of the Information and Privacy Commissioner, June 16, 2014.

Ciriani, V., S. De Capitani di Vimercati, S. Foresti, and P. Samarati. “k-Anonymity.” In Secure Data Management in Decentralized Systems, edited by Ting Yu and Sushil Jajodia. New York: Springer, 2007.

Dalenius, Tore. “Towards a Methodology for Statistical Disclosure Control.” Statistik Tidskrift, vol. 15, 1977, pp. 429-444.

Domingo-Ferrer, Josep, and Josep Maria Mateo-Sanz. “Practical Data-oriented Microaggregation for Statistical Disclosure Control.” IEEE Transactions on Knowledge and Data Engineering, vol. 14, no. 1 (2002), pp. 189-201.

Domingo-Ferrer, Josep, and Vicenc Torra. “Disclosure Risk Assessment in Statistical Microdata Protection via Advanced Record Linkage.” Statistics and Computing, vol. 13, 2003, pp. 343–354.

Duncan, George T., Mark Elliot, and Juan-Jose Salazar-Gonzalez. Statistical Confidentiality: Principles and Practice. New York: Springer, 2011.

Duncan, George T., and Diane Lambert. “The Risk of Disclosure for Microdata.” Journal of Business and Economic Statistics, vol. 7, no. 2, April 1989, pp. 207-217.

Dwork, Cynthia, and Moni Naor. “On the Difficulties of Disclosure Prevention in Statistical Databases or the Case for Differential Privacy.” Journal of Privacy and Confidentiality, vol. 2, no. 1, 2010, pp. 93-107.

Dwork, Cynthia, and Adam Smith. “Differential Privacy for Statistics: What We Know and What We Want to Learn.” Journal of Privacy and Confidentiality, vol. 1, no. 2 (2009), pp. 135-154.

El Emam, Khaled, and Fida Kamal Dankar. “Protecting Privacy Using k-Anonymity.” Journal of the American Medical Informatics Association, vol. 15, no. 5, September/October 2008, pp. 627-637.

El Emam, Khaled, Elizabeth Jonker, Luk Arbuckle, and Bradley Malin. “A Systematic Review of Re-Identification Attacks on Health Data.” PLoS ONE, vol. 6, no. 12, December 2011, pp. 1-12.

Federal Committee on Statistical Methodology. “Report on Statistical Disclosure Limitation Methodology.” Statistical Policy Working Paper 22 (second version). Washington, DC: Office of Information and Regulatory Affairs, Office of Management and Budget, 2005.

Fellegi, Ivan P., and Alan B. Sunter. “A Theory for Record Linkage.” Journal of the American Statistical Association, vol. 64, 1969, pp. 1183-1210.

Golle, Phillippe. “Revising the Uniqueness of Simple Demographics in the U.S. Population.” Palo Alto, CA: Palo Alto Research Center, 2006.

Gostin, L. O. “Health Information Privacy.” Cornell Law Review, vol. 80, 1995, pp. 451–528.

Gouweleeuw, J.M., P. Kooiman, L.C. Willenborg, and P.P. DeWolf. “Post Randomisation for Statistical Disclosure Control: Theory and Implementation.” Research paper no. 9731. Voorburg, Netherlands: Statistics Netherlands, 1997.

Hundepool, A., J. Domingo-Ferrer, L. Franconi, S. Giessing, R. Lenz, J. Naylor, E.S. Nordholt, G. Seri, and P.P. de Wolf. Handbook on Statistical Disclosure Control. A Network Excellence in the European Statistical System in the Field of Statistical Disclosure Control (ESSNet SDC). Hoboken, NJ: Wiley, January 2010.

Kinney, Satkartar K., Alan F. Karr, and Joe Fred Gonzalez, Jr. “Data Confidentiality: The Next Five Years Summary and Guide to Papers.” Journal of Privacy and Confidentiality, vol. 1, no. 2, 2009, pp. 125-134.

Kwok, Peter, and Deborah Lafky. “Harder Than You Think: A Case Study of Re-Identification Risk of HIPAA-Compliant Records.” Proceedings of the Joint Statistical Meetings. Alexandria, VA: American Statistical Association, 2011.

Lane, Julia and Claudia Schur. “Balancing Access to Health Data and Privacy: A Review of the Issues and Approaches for the Future.” Health Services Research, vol. 45, no. 5, Part II, October 2010, pp. 1456-1467.

Machanavajjhala, Ashwin, Johannes Gehrke, Daniel Kifer, and Muthuramakrishnan Venkitasubramaniam. “l-Diversity: Privacy Beyond k-Anonymity.” Cornell Computer Science Department Technical Report. Ithaca, NY: Cornell University, 2005.

Malin, Bradley. “Betrayed by My Shadow: Learning Data Identify via Trail Matching.” Journal of Privacy Technology, June 9, 2005.

Marsh, C., C. Skinner, S. Arber, B. Penhale, S. Openshaw, J. Hobcraft, D. Lievesley, and N. Walford. “The Case for Samples of Anonymized Records from the 1991 Census.” Journal of the Royal Statistical Society, Series A, vol. 154, 1991, pp. 305-340.

Narayanan, A. and V. Shmatikov. “Robust De-anonymization of Large Spare Datasets. Proceedings of the IEEE Symposium on Security and Privacy, 2008, pp. 111-125.

National Research Council. Expanding Access to Research Data: Reconciling Risks and Opportunities. Panel on Data Access for Research Purposes, Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press, 2005.

Office of Management and Budget, Executive Office of the President. “Memorandum Number M-13-13: Open Data Policy––Managing Information as an Asset.” Washington, DC: OMB, May 9, 2013. Available at Accessed July 15, 2013.

Oganian, A., J. Reiter, and A. Karr. “Verification Servers: Enabling Analysts to Assess the Quality of Inferences from Public Use Data.” Computational Statistics and Data Analysis, vol. 53, no. 4, 2009, pp. 1475-1482.

Pozen, D.E. “The Mosaic Theory, National Security, and the Freedom of Information Act.” The Yale Law Journal, December 2005, pp. 628–679.

Prada, S.I., C. Gonzalez, J. Borton, J. Fernandes-Huessy, C. Holden, E. Hair, and T. Mulcahy. “Avoiding Disclosure of Individually Identifiable health Information: A Literature Review.” SAGE Open, December 2011, pp. 1–16.

Purdam, K. and M.J. Elliot. “A Case Study of the Impact of Statistical Disclosure Control on Data Quality in the Individual UK Samples of Anonymised Records.” Environmental Planning, Vol. A 39, 2007, pp. 1101-1118.

Purdam, K. and M.J. Elliot. “An Evaluation of the Availability of Public Data Sources Which Could be Used for Identification Purposes—A Europe Wide Perspective.” CASC Project. University of Manchester, Manchester, 2002.

Rothstein, M.A. “Is Deidentification Sufficient to Protect Health Privacy in Research?” The American Journal of Bioethics, 10:9, 2010, pp. 3-11.

Rubin, Donald B. “Discussion of Statistical Disclosure Limitation.” Journal of Official Statistics, vol. 9, no. 2, 1993, pp. 461-468.

Shatto, Andy. “CMS Program Data.” Presentation to the Council of Professional Associations on Federal Statistics, Washington, DC, June 6, 2014.

Shlomo, Natalie. “Releasing Microdata: Disclosure Risk Estimation, Data Masking, and Assessing Utility.” Journal of Privacy and Confidentiality, vol. 2, no. 1, 2010, pp. 73-91.

Singh, Avinash C. “Maintaining Analytic Utility while Protecting Confidentiality of Survey and Nonsurvey Data.” Journal of Privacy and Confidentiality, vol. 1, no. 2, 2009, pp. 155-182.

Singh, A.C., F. Yu, and G.H. Dunteman. “MASSC: A New Data Mask for Limiting Statistical Information Loss and Disclosure.” In Work Session on Statistical Data Confidentiality 2003, Monographs in Official Statistics, edited by H. Linden, J. Riecan, and L. Belsby, pages 373-394. Luxemburg, Belgium: Eurostat, 2004.

Skinner, C.J. and M.J. Elliot. “A Measure of Disclosure Risk for Microdata.” Journal of the Royal Statistical Society, Series B, vol. 64, 2002, pp. 855-867.

Sweeney, Latanya. “Weaving Technology and Policy Together to Maintain Confidentiality.” Journal of Law, Medicine & Ethics, vol. 25 (1997), pp. 98-110.

Sweeney, Latanya. “Uniqueness of Simple Demographics in the U.S. Population.” Technical report. Pittsburgh, PA: Carnegie Mellon University, 2000.

Sweeney, Latanya. “k-Anonymity: A Model for Protecting Privacy.” International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, vol. 10, no. 5, 2002, pp. 557-570.

Sweeney, Latanya, Akua Abu, and Julia Winn. “Identifying Participants in the Personal Genome Project by Name.” Manuscript, no date.

Torra, Vicenc. “Towards the Re-identification of Individuals in Data Files with Non-common Variables. In Proceedings of the Sixth International Conference on Soft Computing. Iizuka, Japan, 2000.

Torra, Vicenc, John Abowd, and Josep Domingo-Ferrer. “Using Mahalanobis Distance-based Record Linkage for Disclosure Risk Assessment.” Lecture Notes in Computer Science, vol. 4302, 2006, pp. 233-242.

U.S. Government Accountability Office. “Information Resellers: Consumer Privacy Framework Needs to Reflect Changes in Technology and the Marketplace.” Document number GAO-13-663. Washington, DC: GAO, September 2013.

Woo, Mi-Ja, Jerome P. Reiter, Anna Oganian, and Alan F. Karr. “Global Measures of Data Utility for Microdata Masked for Disclosure Limitation.” Journal of Privacy and Confidentiality, vol. 1, no. 1, 2009, pp. 111-124.

Zayatz, Laura. “New Ways to Provide More and Better Data to the Public While Still Protecting Confidentiality.” Proceedings of the Joint Statistical Meetings, Section on Survey Research Methods. Alexandria, VA: American Statistical Association, 2008.

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