Anonymizing set-valued social data

Shyue Liang Wang, Yu Chuan Tsai, Hung-Yu Kao, Tzung Pei Hong

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

4 Citations (Scopus)

Abstract

The increasing popularity of social networks has generated tremendous amount of data to be exploited for commercial, research and many other valuable applications. However, the release of these data has raised an issue that personal privacy may be breached. Current practices of simply removing all identifiable personal information (such as names and social security numbers) before releasing the data is insufficient. More effective anonymization techniques are required. In this work, we propose a k-anonymization-based technique on set-valued network node data. The proposed algorithm is based on the principle of minimizing the number of addition and deletion operations to achieve k-anonymity. Numerical experiments on real dataset show that it requires less number of operations than current suppression-based approach.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010
Pages809-812
Number of pages4
DOIs
Publication statusPublished - 2010 Dec 1
Event2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010 - Hangzhou, China
Duration: 2010 Dec 182010 Dec 20

Publication series

NameProceedings - 2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010

Other

Other2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010
CountryChina
CityHangzhou
Period10-12-1810-12-20

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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