TMk-anonymity: Perturbation-based data anonymization method for improving effectiveness of secondary use

Taichi Nakamura, Hiroaki Nishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The recent emergence of smartphones, cloud computing, and the Internet of Things has brought about the explosion of data creation. By collating and merging these enormous data with other information, services that use information become more sophisticated and advanced. However, at the same time, the consideration of privacy violations caused by such merging is indispensable. Various anonymization methods have been proposed to preserve privacy. The conventional perturbation-based anonymization method of location data adds comparatively larger noise, and the larger noise makes it difficult to utilize the data effectively for secondary use. In this research, to solve these problems, we first clarified the definition of privacy preservation and then propose TMfc-anonymity according to the definition.

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationIECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3138-3143
Number of pages6
ISBN (Electronic)9781509066841
DOIs
Publication statusPublished - 2018 Dec 26
Event44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 - Washington, United States
Duration: 2018 Oct 202018 Oct 23

Publication series

NameProceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

Conference

Conference44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
CountryUnited States
CityWashington
Period18/10/2018/10/23

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Keywords

  • Anonymization
  • Pertur k-anonymity
  • Pk-anonymity
  • Privacy preservation
  • TMk-anon

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Control and Optimization

Cite this

Nakamura, T., & Nishi, H. (2018). TMk-anonymity: Perturbation-based data anonymization method for improving effectiveness of secondary use. In Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society (pp. 3138-3143). [8592838] (Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECON.2018.8592838