Skip to main content
SpringerLink
Log in

Anonymization Techniques

  • Living reference work entry
  • First Online:
Encyclopedia of Big Data

  • 273 Accesses

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

Access this chapter

Log in via an institution

Institutional subscriptions

Further Reading

  • Dwork, C. (2006). Differential privacy. In Automata, languages and programming. Berlin: Springer.

    Google Scholar 

  • Li, Ninghui, et al. (2007). t-Closeness: Privacy beyond k-anonymity and l-diversity. IEEE 23rd International Conference on Data Engineering, 7.

    Google Scholar 

  • Machanavajjhala, A., et al. (2007). l-diversity: Privacy beyond k-anonymity. ACM Transactions on Knowledge Discovery from Data, 1(1), Article 3, 1–12.

    Google Scholar 

  • Sweeney, L. (2002). k-anonymity: A Model for Protecting Privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(5).

    Google Scholar 

  • The European Parliament and of the Council Working Party. (2014). Opinion 05/2014 on anonymisation techniques. http://ec.europa.eu/justice/data-protection/article-29/documentation/opinion-recommendation/files/2014/wp216_en.pdf. Retrieved on 29 Dec 2014.

Download references

Author information

Authors and Affiliations

  1. North Carolina A&T State University, 1601 E Market St, Greensboro, NC, 27401, USA

    Mick Smith

  2. Information Technology Laboratory, US Army Engineer Research and Development Center, 3909 Halls Ferry Rd, Vicksburg, MS, 39180, USA

    Rajeev Agrawal

Authors
  1. Mick Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rajeev Agrawal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mick Smith .

Editor information

Editors and Affiliations

  1. School of Policy, Government and International Affairs, George Mason University, Fairfax, Virginia, USA

    Laurie A. Schintler

  2. School of Policy, Government and International Affairs, George Mason University, Fairfax, Virginia, USA

    Connie L. McNeely

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this entry

Cite this entry

Smith, M., Agrawal, R. (2017). Anonymization Techniques. In: Schintler, L., McNeely, C. (eds) Encyclopedia of Big Data. Springer, Cham. https://doi.org/10.1007/978-3-319-32001-4_9-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-32001-4_9-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32001-4

  • Online ISBN: 978-3-319-32001-4

  • eBook Packages: Springer Reference Business and ManagementReference Module Humanities and Social SciencesReference Module Business, Economics and Social Sciences

Publish with us

Policies and ethics

Search

Navigation