Skip to main content
SpringerLink
Log in
Book cover

International Workshop on Privacy, Security, and Trust in KDD

PInKDD 2008: Privacy, Security, and Trust in KDD pp 7–24Cite as

Geocode Matching and Privacy Preservation

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 5456))

Abstract

Geocoding is the process of matching addresses to geographic locations, such as latitudes and longitudes, or local census areas. In many applications, addresses are the key to geo-spatial data analysis and mining. Privacy and confidentiality are of paramount importance when data from, for example, cancer registries or crime databases is geocoded. Various approaches to privacy-preserving data matching, also called record linkage or entity resolution, have been developed in recent times. However, most of these approaches have not considered the specific privacy issues involved in geocode matching. This paper provides a brief introduction to privacy-preserving data and geocode matching, and using several real-world scenarios the issues involved in privacy and confidentiality for data and geocode matching are illustrated. The challenges of making privacy-preserving matching practical for real-world applications are highlighted, and potential directions for future research are discussed.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. US Federal Geographic Data Committee. Homeland Security and Geographic Information Systems: How GIS and mapping technology can save lives and protect property in post-September 11th America. Public Health GIS News and Information (52), 21–23 (May 2003)

    Google Scholar 

  2. Christen, P., Goiser, K.: Quality and complexity measures for data linkage and deduplication. In: Guillet, F., Hamilton, H.J. (eds.) Quality Measures in Data Mining. Studies in Computational Intelligence, vol. 43, pp. 127–151. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  3. Winkler, W.E.: Overview of record linkage and current research directions. Technical Report RRS2006/02, US Bureau of the Census (2006)

    Google Scholar 

  4. Elmagarmid, A.K., Ipeirotis, P.G., Verykios, V.S.: Duplicate record detection: A survey. IEEE Transactions on Knowledge and Data Engineering 19(1), 1–16 (2007)

    Article  Google Scholar 

  5. Kelman, C.W., Bass, J.A., Holman, D.: Research use of linked health data – A best practice protocol. ANZ Journal of Public Health 26(3), 251–255 (2002)

    Google Scholar 

  6. Jonas, J., Harper, J.: Effective counterterrorism and the limited role of predictive data mining. Policy Analysis (584) (2006)

    Google Scholar 

  7. Wang, G., Chen, H., Xu, J.J., Atabakhsh, H.: Automatically detecting criminal identity deception: An adaptive detection algorithm. IEEE Transactions on Systems, Man and Cybernetics (Part A) 36(5), 988–999 (2006)

    Article  Google Scholar 

  8. Bhattacharya, I., Getoor, L.: Collective entity resolution in relational data. ACM Transactions on Knowledge Discovery from Data (TKDD) 1(1) (2007)

    Google Scholar 

  9. Hernandez, M.A., Stolfo, S.J.: Real-world data is dirty: Data cleansing and the merge/purge problem. Data Mining and Knowledge Discovery 2(1), 9–37 (1998)

    Article  Google Scholar 

  10. Churches, T., Christen, P., Lim, K., Zhu, J.: Preparation of name and address data for record linkage using hidden Markov models. BioMed Central Medical Informatics and Decision Making 2(9) (2002)

    Google Scholar 

  11. Baxter, R., Christen, P., Churches, T.: A comparison of fast blocking methods for record linkage. In: ACM KDD Workshop on Data Cleaning, Record Linkage and Object Consolidation, Washington, DC (2003)

    Google Scholar 

  12. Christen, P.: Febrl – An open source data cleaning, deduplication and record linkage system with a graphical user interface. In: ACM International Conference on Knowledge Discovery and Data Mining, Las Vegas, pp. 1065–1068 (2008)

    Google Scholar 

  13. Cohen, W.W., Ravikumar, P., Fienberg, S.E.: A comparison of string distance metrics for name-matching tasks. In: IJCAI Workshop on Information Integration on the Web, Acapulco, pp. 73–78 (2003)

    Google Scholar 

  14. Christen, P.: A comparison of personal name matching: Techniques and practical issues. In: IEEE ICDM Workshop on Mining Complex Data, Hong Kong, pp. 290–294 (2006)

    Google Scholar 

  15. Christen, P.: Automatic record linkage using seeded nearest neighbour and support vector machine classification. In: ACM International Conference on Knowledge Discovery and Data Mining, Las Vegas, pp. 151–159 (2008)

    Google Scholar 

  16. Clarke, D.: Practical introduction to record linkage for injury research. Injury Prevention 10, 186–191 (2004)

    Article  Google Scholar 

  17. Christen, P., Willmore, A., Churches, T.: A probabilistic geocoding system utilising a parcel based address file. In: Williams, G.J., Simoff, S.J. (eds.) Data Mining. LNCS (LNAI), vol. 3755, pp. 130–145. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  18. Paull, D.: A geocoded national address file for Australia: The G-NAF what, why, who and when? PSMA Australia Limited, Griffith, ACT, Australia (2003), http://www.g-naf.com.au/

  19. Cayo, M.R., Talbot, T.O.: Positional error in automated geocoding of residential addresses. International Journal of Health Geographics 2(10) (2003)

    Google Scholar 

  20. Brownstein, J.S., Cassa, C., Kohane, I.S., Mandl, K.D.: Reverse geocoding: Concerns about patient confidentiality in the display of geospatial health data. In: AMIA Annual Symposium Proceedings 2005, p. 905 (2005)

    Google Scholar 

  21. Brownstein, J.S., Cassa, C., Mandl, K.D.: No place to hide–reverse identification of patients from published maps. New England Journal of Medicine 355(16), 1741–1742 (2006)

    Article  Google Scholar 

  22. Curtis, A.J., Mills, J.W., Leitner, M.: Spatial confidentiality and GIS: Re-engineering mortality locations from published maps about Hurricane Katrina. International Journal of Health Geographics 5(1), 44–56 (2006)

    Article  Google Scholar 

  23. Australian Attorney-General’s Department, Standing Committee of Attorney’s-General: Model criminal law officers’ committee: Final report on identity crime. Canberra (March 2008)

    Google Scholar 

  24. Chaytor, R., Brown, E., Wareham, T.: Privacy advisors for personal information management. In: SIGIR Workshop on Personal Information Management, Seattle, Washington, pp. 28–31 (2006)

    Google Scholar 

  25. Fienberg, S.E.: Privacy and confidentiality in an e-Commerce world: Data mining, data warehousing, matching and disclosure limitation. Statistical Science 21(2), 143–154 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  26. Sweeney, L.: K-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 10(5), 557–570 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  27. Christen, P.: Privacy-preserving data linkage and geocoding: Current approaches and research directions. In: IEEE ICDM Workshop on Privacy Aspects of Data Mining, Hong Kong, pp. 497–501 (2006)

    Google Scholar 

  28. Sweeney, L.: Privacy-enhanced linking. ACM SIGKDD Explorations 7(2), 72–75 (2005)

    Article  Google Scholar 

  29. Christen, P., Churches, T.: Secure health data linkage and geocoding: Current approaches and research directions. In: National e-Health Privacy and Security Symposium, Brisbane, Australia (2006)

    Google Scholar 

  30. Wartell, J., McEwen, T.: Privacy in the information age: A guide for sharing crime maps and spatial data. Institute for Law and Justice, NCJ 188739 (July 2001)

    Google Scholar 

  31. Rushton, G., Armstrong, M.P., Gittler, J., Greene, B.R., Pavlik, C.E., West, M.M., Zimmerman, D.L.: Geocoding in cancer research – A review. American Journal of Preventive Medicine 30(2S), 16–24 (2006)

    Article  Google Scholar 

  32. Rivest, R.L.: Chaffing and winnowing: Confidentiality without encryption. MIT Lab for Computer Science (1998), http://theory.lcs.mit.edu/~rivest/chaffing.txt

  33. Churches, T.: A proposed architecture and method of operation for improving the protection of privacy and confidentiality in disease registers. BioMed. Central Medical Research Methodology 3(1) (2003)

    Google Scholar 

  34. Bouzelat, H., Quantin, C., Dusserre, L.: Extraction and anonymity protocol of medical file. In: AMIA Fall Symposium, pp. 323–327 (1996)

    Google Scholar 

  35. Dusserre, L., Quantin, C., Bouzelat, H.: A one way public key cryptosystem for the linkage of nominal files in epidemiological studies. Medinfo. 8(644–7) (1995)

    Google Scholar 

  36. Quantin, C., Bouzelat, H., Allaert, F.A., Benhamiche, A.M., Faivre, J., Dusserre, L.: Automatic record hash coding and linkage for epidemiological follow-up data confidentiality. Methods of Information in Medicine 37(3), 271–277 (1998)

    Google Scholar 

  37. Quantin, C., Bouzelat, H., Allaert, F.A., Benhamiche, A.M., Faivre, J., Dusserre, L.: How to ensure data quality of an epidemiological follow-up: Quality assessment of an anonymous record linkage procedure. International Journal of Medical Informatics 49(1), 117–122 (1998)

    Article  Google Scholar 

  38. Quantin, C., Bouzelat, H., Dusserre, L.: Irreversible encryption method by generation of polynomials. Medical Informatics and the Internet in Medicine 21(2), 113–121 (1996)

    Article  Google Scholar 

  39. Schneier, B.: Applied cryptography: Protocols, algorithms, and source code in C, 2nd edn. John Wiley & Sons, Inc., New York (1995)

    MATH  Google Scholar 

  40. Ravikumar, P., Cohen, W.W., Fienberg, S.E.: A secure protocol for computing string distance metrics. In: IEEE ICDM Workshop on Privacy and Security Aspects of Data Mining, Brighton, UK (2004)

    Google Scholar 

  41. Atallah, M.J., Kerschbaum, F., Du, W.: Secure and private sequence comparisons. In: ACM Workshop on Privacy in the Electronic Society, Washington DC, pp. 39–44 (2003)

    Google Scholar 

  42. O’Keefe, C.M., Yung, M., Gu, L., Baxter, R.: Privacy-preserving data linkage protocols. In: ACM Workshop on Privacy in the Electronic Society, Washington DC, pp. 94–102 (2004)

    Google Scholar 

  43. Churches, T., Christen, P.: Some methods for blindfolded record linkage. BioMed. Central Medical Informatics and Decision Making 4(9) (2004)

    Google Scholar 

  44. Al-Lawati, A., Lee, D., McDaniel, P.: Blocking-aware private record linkage. In: International Workshop on Information Quality in Information Systems, Baltimore, pp. 59–68 (2005)

    Google Scholar 

  45. Inan, A., Kantarcioglu, M., Bertino, E., Scannapieco, M.: A hybrid approach to private record linkage. In: IEEE International Conference Data Engineering, pp. 496–505 (2008)

    Google Scholar 

  46. Christen, P.: Automatic training example selection for scalable unsupervised record linkage. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds.) PAKDD 2008. LNCS (LNAI), vol. 5012, pp. 511–518. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  47. Guisado-Gamez, J., Prat-Perez, A., Nin, J., Muntes-Mulero, V., Larriba-Pey, J.L.: Parallelizing record linkage for disclosure risk assessment. In: Privacy in Statistical Databases, Istanbul, Turkey. LNCS, vol. 5262, pp. 190–202. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  48. Christen, P., Gayler, R.: Towards scalable real-time entity resolution using a similarity-aware inverted index approach. In: AusDM 2008, CRPIT, Glenelg, Australia, vol. 87, pp. 51–60 (2008)

    Google Scholar 

  49. Winkler, W.E.: Masking and re-identification methods for public-use microdata: Overview and research problems. In: Domingo-Ferrer, J., Torra, V. (eds.) PSD 2004. LNCS, vol. 3050, pp. 216–230. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  50. Malin, B., Sweeney, L.: A secure protocol to distribute unlinkable health data. In: American Medical Informatics Association 2005 Annual Symposium, Washington DC, pp. 485–489 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, The Australian National University, Canberra, ACT 0200, Australia

    Peter Christen

Authors
  1. Peter Christen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Yahoo! Research Barcelona, Avinguda Drive 177, 08018, Barcelona, Spain

    Francesco Bonchi

  2. Department of Computer Science and Communication, University of Insubria, 22100, Varese, Italy

    Elena Ferrari

  3. 311 Computer Science Building, 500W. 15th St., MO 65409, Rolla, USA

    Wei Jiang

  4. Department of Biomedical Informatics, Vanderbilt University, TN 37203, nashville, USA

    Bradley Malin

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Christen, P. (2009). Geocode Matching and Privacy Preservation. In: Bonchi, F., Ferrari, E., Jiang, W., Malin, B. (eds) Privacy, Security, and Trust in KDD. PInKDD 2008. Lecture Notes in Computer Science, vol 5456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01718-6_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-01718-6_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01717-9

  • Online ISBN: 978-3-642-01718-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation