- Published on: 2016-05-10
- Event hosted by: NCRM
- Keywords: research methods | measuring disclosure risk | data linkage |
- To cite this resource:
Elliot, M. (2019) Anonymisation: theory and practice. National Centre for Research Methods online learning resource. Available at http://www.ncrm.ac.uk/resources/online/anonymisation-theory_and_practice/ [ accessed: February 21, 2019]'
Here are the slides in Microsoft Powerpoint format. You may want to explore the slides or download the entire presentation by clicking the link below
These video resources were recorded on 2016-05-10 by the National Centre for Research Methods (NCRM) at the University of Southampton.
Powerpoint presentations (PDF)
- Slide [1/3]:anonymisation theory and practice.pdf
- Slide [2/3]:Anonymisation decision making framework.pdf
- Slide [3/3]:statistical discolosure control.pdf
Video Transcripts (PDF)
- Transcript [1/2]:Anonymisation_theory_and_practice.pdf
- Transcript [2/2]:Anonymisation_decision_making_framework.pdf
Related datasets and other links
- DE MONTJOYE, Y. A., RADAELLI, L., & SINGH, V. K. (2015) Unique in the shopping mall: On the reidentifiability of credit card metadata; Science, 347(6221): 536-539, available at: http://tinyurl.com/UNIQ-CC [accessed 30/5/16].
- DOBRA, A. & FIENBERG, S. E. (2000) Bounds for cell entries in contingency tables given marginal totals and decomposable graphs; in Proceedings of the National Academy of Sciences, 97(22): 11885-11892, available at: http://tinyurl.com/BNDS-DECOM [accessed 30/5/16].
- DOBRA, A. & FIENBERG, S. E. (2001) Bounds for cell entries in contingency tables induced by fixed marginal totals; Statistical Journal of the United Nations Economic Commission for Europe, 18(4): 363-371, available at: http://tinyurl.com/BNDS-MARGINAL [accessed 30/5/16].
- DOMINGO-FERRER, J, SANCHEZ, D., & SORIA-COMAS, J. (2016) Database Anonymization: Privacy Models, Data Utility, and Microaggregation-based Inter-model Connections; Synthesis Lectures on Information Security, Privacy, & Trust 15: Morgan & Claypool, DOI: 10.2200/S00690ED1V01Y201512SPT015. DOYLE, P., LANE, J. I., THEEUWES, J. M. & ZAYATZ, L. V. (eds.) (2001) Confidentiality, Disclosure, and Data Access: Theory and Practical Applications for Statistical Agencies. Amsterdam: Elsevier, 135-166.
- DUNCAN, G. T., FIENBERG, S. E., KRISHNAN, R., PADMAN, R., & ROEHRIG, S. F. (2001) Disclosure limitation methods and information loss for tabular data; In Doyle, P., Lane, J. I., Theeuwes, J. M., & Zayatz, L. V. (eds.) Confidentiality, Disclosure, and Data Access: Theory and Practical Applications for Statistical Agencies. Amsterdam: Elsevier, 135-166.
- DUNCAN, G. T., ELLIOT, M. J., & SALAZAR-GONZALEZ, J. J. (2011) Statistical Confidentiality. New York: Springer.
- ELAMIR, E.A. & SKINNER, C. (2006) Record level measures of disclosure risk for survey microdata; Journal of Official Statistics, 22(3): 525, available at: http://tinyurl.com/REC-RISK [accessed 30/5/16].
- EL EMAM, K. (2013) Guide to the De-Identification of Personal Health Information. Boca Raton, Florida: Auerbach Publications (CRC Press).
- EL EMAM, K. (ed.) (2013) Risky Business: Sharing Health Data while Protecting Privacy. Bloomington, Indiana: Trafford Publishing.
- EL EMAM, K. & ARBUCKLE L. (2014) Anonymizing Health Data 2nd Edition. Sebastapol, California: O'Reilly media.
- ELLIOT, M. J. (1996) Attacks on Confidentiality Using the Samples of Anonymised Records; In Proceedings of the Third International Seminar on Statistical Confidentiality. Bled, Slovenia, October 1996. Ljubljana: Statistics Slovenia-Eurostat.
- ELLIOT, M. J. (2000) DIS: A new approach to the measurement of statistical disclosure risk; Risk Management, 2: 39-48, DOI:10.1057/palgrave.rm.8240067. %ELLIOT, M. J. (2001) Advances in data intrusion simulation: A vision for the future of data release; Statistical Journal of the United Nations Economic Commission for Europe, 18(4): 383-391.
- ELLIOT, M. J. & DALE, A. (1999) Scenarios of Attack: The Data Intruder's Perspective on Statistical Disclosure Risk; Netherlands Official Statistics, Spring 1999: 6-10, available at: http://tinyurl.com/ATTACK-SCENARIO [accessed 30/5/16]. %ELLIOT, M. J., DIBBEN, C., GOWANS, H., MACKEY, E., LIGHTFOOT, D., O'HARA, K., & PURDAM, K. (2015) Functional Anonymisation: The crucial role of the data environment in determining the classification of data as (non-) personal; CMIST work paper 2015-2 available at http://tinyurl.com/FUNC-ANON [accessed 27/5/2016].
- ELLIOT, M. J., MACKEY, E., O'SHEA S., TUDOR, C. & SPICER, K. (2016) Open Data or End User License: A Penetration Test; Journal of Official Statistics, 32(2): 329-348, DOI: 10.1515/JOS-2016-0019.
- FIENBERG, S.E. (2005) Confidentiality and Disclosure Limitation; In Kempf-Leonard K. (ed.), Encyclopaedia of Social Measurement volume 3. New York: Elsiever.
- HUNDEPOOL, A., DOMINGO-FERRER, J., FRANCONI, L., GIESSING, S., NORDHOLT, E. S., SPICER, K. & DE WOLF, P. P. (2012) Statistical Disclosure Control. London: John Wiley & Sons.
- LANE, J., STODDEN, V., BENDER, S. & NISSENBAUM, H. (Eds.) (2014) Privacy, Big Data, and the Public Good. Cambridge: Cambridge University Press.
- MACKEY, E. & ELLIOT, M. J. (2013) Understanding the Data Environment; XRDS: Crossroads, 20 (1): 37-39.
- NISSENBAUM, H. (2004) Privacy as contextual integrity; Washington Law Review, 79 (119): 101-139, available at: http://tinyurl.com/j8xut58 [accessed 30/5/2016].
- NISSENBAUM, H. (2010) Privacy in Context: Technology, Policy, and the Integrity of Social Life. Palo Alto, CA: Stanford University Press.
- SAMARATI, P. (2001) Protecting respondents' identities in microdata release; IEEE Transactions on Knowledge and Data Engineering, 13(6): 1010-1027.
- SAMARATI, P. & SWEENEY, L. (1998) Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression. Washington: SRI International, available at: http://tinyurl.com/sam-swe-kanon [accessed 28/5/16].
- SANCHEZ, D., MARTINEZ, S. & DOMINGO-FERRER, J. (2016) Comment on 'Unique in the shopping mall: On the reidentifiability of credit card metadata'; Science 351 (6279): 1274.
- SKINNER, C. J. & ELLIOT, M. J. (2002) A measure of disclosure risk for microdata; Journal of the Royal Statistical Society: series B (statistical methodology), 64(4): 855-867, DOI: 10.1111/1467-9868.00365.
- SMITH, D. & ELLIOT, M. (2008) A Measure of Disclosure Risk for Tables of Counts; Transactions on Data Privacy, 1(1): 34-52, available at: http://www.tdp.cat/issues/tdp.a003a08.pdf [accessed 30/5/16].
- WILLENBORG, L. & DE WAAL, T. (2001) Elements of Disclosure Control. Springer: New York.
Related research areas (available items)
All relevant references can be listed here along with browsable links to other existing resources in NCRM
Allison, P. D. ( 2005). Fixed Effects Regression Methods for Longitudinal Data Using SAS. Cary, NC.:SAS Institute Inc.
Bollen, K. (1989). Structural Equations with Latent Variables. New York: Wiley.
Bailey, C. (2001) Geographers doing household research: Intrusive research and moral accountability, Area, 33, 1, 107-109.
Bakardjieva, M. and Feenberg, A. (2001) Involving the virtual subject, Ethics and Information Technology, 2, 4, 233-240.
Barnes, S. B. (2004) Issues of attribution and identification in online social research, in Johns, M. D., Chen, S. S. and Hall, G. J. (Eds.) (2004) Online Social Research: Methods, Issues, and Ethics. New York. Peter Lang. pp. 203-222.
Recommended readings etc. (which uathor may deem appropriate (could be event, NCRM resource, book chapter etc.
Bulloch, SarahUsing Structural Equation Modelling to re-examine the association between gender and social trust: the search for measurement equivalence. In: NCRM Research Methods Festival 2008, 30th June - 3rd July 2008, St Catherine's College, Oxford.Download from http://eprints.ncrm.ac.uk/303/
Mehta, P. & Neale, M. (2005) People are variables too: Multilevel structural equations modeling. Psychological Methods, 10, 259-284. Download from http://statmodel.com/download/mehtaneale.PDF
Preacher, K., Zyphur, M. & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15, 209-233. Download from http://statmodel.com/download/pzz_012610_for_web.pdf
Past videos by Mark Elliot
Find Mark Elliot elsewhere on NCRM
- What is AI (Conference)
- What is Explainable AI (Conference)
- Developing Effective Research proposals (Conference)
- Anonymisation: what is it and how do I do it (Conference)
- Anonymisation theory and practice (Video)
- Statistical disclosure control, basic concepts (Video)
- The Visual Field (Event)
- Creating Data Policy in a Changing Data Landscape: A Workshop (Event)
- WEBINAR: Anonymisation theory and practice (Training)
- The Visual Field (Webinar)
- Streaming into the future: An agenda setting workshop (Event)
Search results based on Mark Elliot's research interests
- Online Data Collection (187)
- Microdata Methods (153)
- Confidentiality and Anonymity (86)
- Statistical Disclosure Control (44)
More like this video tutorials
- Statistical Theory and Methods of Inference (253)
- Quantitative Software (202)
- Quantitative Approaches (other) (194)
- Regression Methods (190)
- Frameworks for Research and Research Designs (other) (136)
- Latent Variable Models (133)
- Structural equation models (79)
- Hypothesis testing research (60)
- Data linkage (50)
- Analysis of administrative data (47)
- SPSS (41)
- Data archiving (40)
Related NCRM training and events materials
- WEBINAR: Anonymisation theory and practice (Training & Events)
- Applied Research Methods with Hidden, Marginal and Excluded Population (Training & Events)
- ADLS Safe Researcher Training - London (Training & Events)
- ADLS Safe Researcher Training - Edinburgh (Training & Events)
- Multiple Regression using SPSS (Training & Events)
- Structural Equation Modelling using Mplus (Training & Events)
Related Audio/Video/Poedcasts/ etc.
About this form
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