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Confidentialising Maps of Mixed Point and Diffuse Spatial Data

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Privacy in Statistical Databases (PSD 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7556))

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Abstract

In this paper we provide an introduction to the area of disseminating spatial data through maps, including an overview of confidentialisation techniques. To date, published methods have focussed on confidentialising maps of spatial point data, mainly in the context of epidemiological and health research. However, maps of spatial data sets of point and diffuse (line and area) records are becoming more important and require confidentialisation in some applications. In this paper we propose a method for confidentialising maps of spatial data sets which include a mixture of point, line and area records. The method combines and adapts traditional non-perturbative disclosure control techniques.

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References

  1. Prime Minister’s Science, Engineering and Innovation Council Working Group on Data for Science: From Data to Wisdom: Pathways to Successful Data Management for Australian Science. Report (2006)

    Google Scholar 

  2. Kamel-Boulos, M., Curtis, A., AbdelMalik, P.: Musings on privacy issues in health research involving disaggregate geographic data about individuals. Int. J. Health Geogr. 46(8), 8 (2009)

    Google Scholar 

  3. VanWey, L., Rindfuss, R., Gutmann, M., Entwisle, B., Balk, D.: Confidentiality and spatially explicit data: Concerns and challenges. P. Natl. A Sci. USA 102, 15337–15342 (2005)

    Article  Google Scholar 

  4. Open Geospatial Consortium, http://www.opengeospatial.org

  5. Machanavajjhala, A., Kifer, D., Abowd, J., Gehrke, J., Vilhuber, L.: Privacy: Theory meets practice on the map. In: IEEE 24th International Conference on Data Engineering, ICDE 2008, pp. 277–286 (April 2008)

    Google Scholar 

  6. European Pollutant Release and Transfer Register, http://prtr.ec.europa.eu

  7. DIRECTIVE 2003/4/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 28 January 2003 on public access to environmental information, eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2003:041:0026:0032:EN:PDF

  8. Australian Government Department of Climate Change and Energy Efficiency, http://www.climatechange.gov.au

  9. Intergovernmental Panel on Climate Change, http://www.ipcc.ch

  10. Australian Government Department of Climate Change and Energy Efficiency: Australian National Greenhouse Accounts National Inventory Report 2010. Technical Report, vol. 1, 320 p. (2012), http://www.climatechange.gov.au

  11. Intergovernmental Panel on Climate Change Guidelines for National Greenhouse Gas Inventories, http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html

  12. Domingo-Ferrer, J., Torra, V. (eds.): PSD 2004. LNCS, vol. 3050. Springer, Heidelberg (2004)

    Google Scholar 

  13. Doyle, P., Lane, J., Theeuwes, J., Zayatz, L. (eds.): Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies. North-Holland, Amsterdam (2001)

    Google Scholar 

  14. Willenborg, L., de Waal, T.: Elements of Statistical Disclosure Control. Lecture Notes in Statistics, vol. 155. Springer (2001)

    Google Scholar 

  15. Gomatam, S., Karr, A., Reiter, J., Sanil, A.: Data dissemination and disclosure limitation in a world without microdata: A risk-utility framework for remote access systems. Stat. Sci. 20, 163–177 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  16. O’Keefe, C., Good, N.: Regression output from a remote analysis system. Data Knowl. Eng. 68, 1175–1186 (2009)

    Article  Google Scholar 

  17. Reiter, J.: New approaches to data dissemination: A glimpse into the future (?). Chance 17, 12–16 (2004)

    Google Scholar 

  18. Sparks, R., Carter, C., Donnelly, J., O’Keefe, C., Duncan, J., Keighley, T., McAullay, D.: Remote access methods for exploratory data analysis and statistical modelling: Privacy-Preserving AnalyticsTM. Comput. Meth. Prog. Bio. 91, 208–222 (2008)

    Article  Google Scholar 

  19. Brandt, M., Zwick, M.: Improvement of data access. The long way to remote data access in Germany. In: Privacy in Statistical Databases Conference PSD (2010), Short paper in CD proceedings

    Google Scholar 

  20. Lucero, J., Zayatz, L., Singh, L., You, J., DePersio, M., Freiman, M.: The Current Stage of the Microdata Analysis System at the U.S. Census Bureau. In: Proc 58th Congress of the International Statistical Institute, ISI 2011 (2011)

    Google Scholar 

  21. Reuter, W.H., Museux, J.-M.: Establishing an Infrastructure for Remote Access to Microdata at Eurostat. In: Domingo-Ferrer, J., Magkos, E. (eds.) PSD 2010. LNCS, vol. 6344, pp. 249–257. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  22. Corscadden, L., Enright, J., Khoo, J., Krsinich, F., McDonald, S., Zeng, I.: Disclosure assessment of analytical output. Statistics New Zealand Preprint (2006)

    Google Scholar 

  23. Honinger, J., Pattloch, D., Voshage, R.: On-site access to micro data: Preserving the treasure, preventing disclosure (2010) (preprint)

    Google Scholar 

  24. Reznek, A.: Disclosure risks in cross-section regression models. In: American Statistical Association 2003 Proceedings of the Section on Government Statistics and Section on Social Statistics, CD, pp. 3444–3451 (2003)

    Google Scholar 

  25. Reznek, A.: Recent confidentiality research related to access to enterprise microdata. In: Prepared for the Comparative Analysis of Enterprise Microdata (CAED) Conference, Chicago IL, USA (2006)

    Google Scholar 

  26. Reznek, A., Riggs, T.L.: Disclosure risks in regression models: Some further results. In: American Statistical Association 2004 Proceedings of the Section on Government Statistics and Section on Social Statistics, CD, pp. 1701–1708 (2004)

    Google Scholar 

  27. Reznek, A., Riggs, T.: Disclosure risks in releasing output based on regression residuals. In: American Statistical Association 2005 Proceedings of the Section on Government Statistics and Section on Social Statistics, CD, pp. 1397–1404 (2005)

    Google Scholar 

  28. Ritchie, F.: Disclosure controls for regression outputs. Mimeo, Office of National Statistics, London (2006)

    Google Scholar 

  29. Ritchie, F.: Disclosure detection in research environments in practice. In: Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality. Number WP. 37 in Topic (iii): Applications, Manchester, UK, United Nations Statistical Commission and Economic Commission for Europe Conference of Europe Statisticians, European Commission Statistical Office of the European Communities (Eurostat), December 17-19 (2007)

    Google Scholar 

  30. Brandt, M., Franconi, L., Gurke, C., Hundepol, A., Lucarelli, M., Mol, J., Ritchie, F., Seri, G., Welpton, R.: Guidelines for the checking of outputs based on microdata research. In: ESSnet SDC, A Network of Excellence in the European Statistical System in the Field of Statistical Disclosure Control (2010), http://neon.vb.cbs.nl/casc/ESSnet/guidelines_on_outputchecking.pdf

  31. Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating noise to sensitivity in private data analysis. In: 3rd IACR Theory of Cryptography Conference, pp. 265–284 (2006)

    Google Scholar 

  32. Dwork, C., Smith, A.: Differential privacy for statistics: What we know and what we want to learn. J. Priv. Confid. 1, 135–154 (2009)

    Google Scholar 

  33. Kifer, D., Machanavajjhala, A.: No free lunch in data privacy. In: Proc. SIGMOD 2011, Athens, Greece, June 12-16, pp. 193–204 (2011)

    Google Scholar 

  34. Barak, B., Chaudhuri, K., Dwork, C., Kale, S., McSherry, F., Talwar, K.: Privacy, accuracy, and consistency too: a holistic solution to contingency table release. In: Proceedings of the 26th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS), pp. 273–282 (2007)

    Google Scholar 

  35. Dwork, C., Lei, J.: Differential privacy and robust statistics. In: Proceedings of the 41st ACM Symposium on Theory of Computing (STOC), pp. 371–380 (2009)

    Google Scholar 

  36. Smith, A.: Asymptotically Optimal and Private Statistical Estimation. In: Garay, J.A., Miyaji, A., Otsuka, A. (eds.) CANS 2009. LNCS, vol. 5888, pp. 53–57. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  37. Shlomo, N.: Statistical disclosure control methods for census frequency tables. Int. Stat. Rev. 75, 199–217 (2007)

    Article  Google Scholar 

  38. Cox, L.: Disclosure risk and data quality. In: Proceedings of the 58th Congress of the International Statistical Institute, Dublin, August 21-26 (2011)

    Google Scholar 

  39. Cox, L.: Confidentiality issues for statistical database query systems. Invited Paper for Joint UNECE/Eurostat Seminar on Integrated Statistical Information Systems and Related Matters (ISIS 2002), Geneva, Switzerland, April 17-19 (2002)

    Google Scholar 

  40. Castro, J.: Minimum-distance controlled perturbation methods for large-scale tabular data protection. Eur. J. Oper. Res. 171, 39–52 (2006)

    Article  MATH  Google Scholar 

  41. Domingo-Ferrer, J., Torra, V.: A critique of the sensitivity rules usually employed for statistical table protection. Int. J. Uncertain Fuzz. 10, 545–556 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  42. Robertson, D.A., Ethier, R.: Cell suppression: Experience and theory. In: Domingo-Ferrer, J. (ed.) Inference Control in Statistical Databases. LNCS, vol. 2316, pp. 8–20. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  43. Fienberg, S.: Statistical perspectives in confidentiality and data access in public health. Stat. Med. 20, 1347–1356 (2001)

    Article  Google Scholar 

  44. Zimmerman, D., Pavlik, C.: Quantifying the Effects of Mask Metadata Disclosure and Multiple Releases on the Confidentiality of Geographically Masked Health Data. In: Geographical Analysis, vol. 40. Blackwell Publishing Inc. (2006)

    Google Scholar 

  45. Armstrong, M., Rushton, G., Zimmerman, D.: Geographically masking health data to preserve confidentiality. Stat. Med. 18, 497–525 (1999)

    Article  Google Scholar 

  46. Brownstein, J., Cassa, C., Kohane, I., Mandl, K.: An unsupervised classification method for inferring original case locations from low-resolution disease maps. Int. J. Health Geogr. 5, 56 (2006)

    Article  Google Scholar 

  47. Curtis, A., Mills, J., Leitner, M.: Spatial confidentiality and GIS: re-engineering mortality locations from published maps about Hurricane Katrina. Int. J. Health Geogr. 5, 44 (2006)

    Article  Google Scholar 

  48. Rasheed, C., Neeman, T.: Mapping farm survey data in rural and regional australia. Australian Bureau of Agricultural and Resource Economics Conference Paper 2000, p. 29 (2000)

    Google Scholar 

  49. Olson, K., Grannis, S., Mandl, K.: Privacy protection versus cluster detection in spatial epidemiology. Am J. Public Health 96, 2002–2008 (2006)

    Article  Google Scholar 

  50. Curtis, A., Mills, J., Agustin, L., Cockburn, M.: Confidentiality risks in fine scale aggregations of health data. Comput. Environ. Urban 35, 57–64 (2011)

    Article  Google Scholar 

  51. Gregorio, D., Dechello, L., Samociuk, H., Kulldorff, M.: Lumping or splitting: seeking the preferred areal unit for health geography studies. Int. J. Health Geogr. 4, 6 (2005)

    Article  Google Scholar 

  52. Cassa, C., Grannis, S., Overhage, J., Mandl, K.: A context-sensitive approach to anonymizing spatial surveillance data: impact on outbreak detection. J. Am. Med. Inform. Assn. 13, 160–165 (2006)

    Article  Google Scholar 

  53. Leitner, M., Curtis, A.: Cartographic guidelines for geographically masking the locations of confidential point data. Cartogr. Persp. 49, 22–39 (2004)

    Google Scholar 

  54. Wieland, S., Cassa, C., Mandl, K., Berger, B.: Revealing the spatial distribution of a disease while preserving privacy. P. Natl. Acad. Sci. USA 105, 17608–17613 (2008)

    Article  Google Scholar 

  55. Hampton, K., Fitch, M., Allshouse, W., Doherty, I., Gesink, D., Leone, P., Serre, M., Miller, W.: Mapping health data: Improved privacy protection with donut method geomasking. Am. J. Epidemiol. 172, 1062–1069 (2010)

    Article  Google Scholar 

  56. Theloke, J., Thiruchittampalam, B., Orlikova, S., Uzbasich, M., Gauger, T.: Methodology development for the spatial distribution of the diffuse emissions in europe. Technical Report 139, European Commission (2009), http://circa.europa.eu/Public/irc/env/e_prtr/library?l=/diffuse_releases_e-prtr/methodology_2011/_EN_1.0_&a=d

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Authors and Affiliations

  1. CSIRO Mathematics, Informatics and Statistics, GPO Box 664, Canberra, ACT, 2601, Australia

    Christine M. O’Keefe

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  1. Christine M. O’Keefe
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Editors and Affiliations

  1. Departament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili UNESCO Chair in Data Privacy, Av. Països Catalans 26, E-43007, Tarragona, Catalonia, Spain

    Josep Domingo-Ferrer

  2. Dipartimento di Ingegneria Elettrica, Elettronica e delle Telecomunicazioni, di tecnologie Chimiche, Automatica e modelli Matematici, Università degli Studi di Palermo, Viale delle Scienze, edificio 9, 90128, Palermo, Italy

    Ilenia Tinnirello

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O’Keefe, C.M. (2012). Confidentialising Maps of Mixed Point and Diffuse Spatial Data. In: Domingo-Ferrer, J., Tinnirello, I. (eds) Privacy in Statistical Databases. PSD 2012. Lecture Notes in Computer Science, vol 7556. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33627-0_18

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  • DOI: https://doi.org/10.1007/978-3-642-33627-0_18

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  • Print ISBN: 978-3-642-33626-3

  • Online ISBN: 978-3-642-33627-0

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