Privacy-Preserving Collaborative Data Anonymization with Sensitive Quasi-Identifiers

Kok Seng Wong, Nguyen Anh Tu, Dinh Mao Bui, Shih Yin Ooi, Myung Ho Kim

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

Abstract

Collaborative anonymization deals with a group of respondents in a distributed environment. Unlike in centralized settings, no respondent is willing to reveal his or her records to any party due to the privacy concerns. This creates a challenge for anonymization, and it requires a level of trust among respondents. In this paper, we study a collaborative anonymization protocol that aims to increase the confidence of respondents during data collection. Unlike in existing works, our protocol does not reveal the complete set of quasi-identifier (QID) to the data collector (e.g., agency) before and after the data anonymization process. Because QID can be both sensitive values and identifying values, we allow the respondents to hide sensitive-QID attributes from other parties. Our protocol ensures that the desired protection level (i.e., k-anonymity) can be verified before the respondents submit their records to the agency. Furthermore, we allow honest respondents to indict a malicious agency if it modifies the intermediate results or not following the protocol faithfully.

Original languageEnglish
Title of host publication2019 12th CMI Conference on Cybersecurity and Privacy, CMI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728128566
DOIs
Publication statusPublished - Nov 2019
Event12th CMI Conference on Cybersecurity and Privacy, CMI 2019 - Copenhagen, Denmark
Duration: Nov 28 2019Nov 29 2019

Publication series

Name2019 12th CMI Conference on Cybersecurity and Privacy, CMI 2019

Conference

Conference12th CMI Conference on Cybersecurity and Privacy, CMI 2019
CountryDenmark
CityCopenhagen
Period11/28/1911/29/19

Keywords

  • Collaborative Anonymization
  • Data Anonymiza-tion
  • Data Privacy
  • k-anonymization
  • Sensitive Quasi-Identifier

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Information Systems and Management

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