research-article

Privacy protection for RFID data

Authors:

Benjamin C. M. Fung,

Bipin C. Desai,

Heng XuAuthors Info & Claims

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

Pages 1528 - 1535

https://doi.org/10.1145/1529282.1529626

Published: 08 March 2009 Publication History

Abstract

Radio Frequency IDentification (RFID) is a technology of automatic object identification. Retailers and manufacturers have created compelling business cases for deploying RFID in their supply chains. Yet, the uniquely identifiable objects pose a privacy threat to individuals. In this paper, we study the privacy threats caused by publishing RFID data. Even if the explicit identifying information, such as name and social security number, has been removed from the published RFID data, an adversary may identify a target victim's record or infer her sensitive value by matching a priori known visited locations and timestamps. RFID data by default is high-dimensional and sparse, so applying traditional K-anonymity to RFID data suffers from the curse of high dimensionality, and would result in poor data usefulness. We define a new privacy model, develop an anonymization algorithm to accommodate special challenges on RFID data, and evaluate its performance in terms of data quality, efficiency, and scalability. To the best of our knowledge, this is the first work on anonymizing high-dimensional RFID data.

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Cited By

Riyana SRiyana N(2024)Ensuring Security and Privacy Preservation for the Publication of Rating DatasetsSN Computer Science10.1007/s42979-024-02690-y5:4Online publication date: 27-Mar-2024
https://doi.org/10.1007/s42979-024-02690-y
Riyana SRiyana NNanthachumphu S(2021)Privacy Preservation Techniques for Sequential Data ReleasingProceedings of the 12th International Conference on Advances in Information Technology10.1145/3468784.3470468(1-9)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1145/3468784.3470468
Riyana SRiyana N(2021)A Privacy Preservation Model for RFID Data-Collections is Highly Secure and More Efficient than LKC-PrivacyProceedings of the 12th International Conference on Advances in Information Technology10.1145/3468784.3469853(1-11)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1145/3468784.3469853
Show More Cited By

Index Terms

Privacy protection for RFID data
1. Information systems
  1. Data management systems
    1. Database administration
  2. Information systems applications

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cover image ACM Conferences

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

March 2009

2347 pages

ISBN:9781605581668

DOI:10.1145/1529282

Conference Chairs:
Sung Y. Shin
South Dakota State University, United States
,
Sascha Ossowski
University Rey Juan Carlos, Spain

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 08 March 2009

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SAC09: The 2009 ACM Symposium on Applied Computing

March 8, 2009 - March 12, 2008

Hawaii, Honolulu

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Riyana SRiyana N(2024)Ensuring Security and Privacy Preservation for the Publication of Rating DatasetsSN Computer Science10.1007/s42979-024-02690-y5:4Online publication date: 27-Mar-2024
https://doi.org/10.1007/s42979-024-02690-y
Riyana SRiyana NNanthachumphu S(2021)Privacy Preservation Techniques for Sequential Data ReleasingProceedings of the 12th International Conference on Advances in Information Technology10.1145/3468784.3470468(1-9)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1145/3468784.3470468
Riyana SRiyana N(2021)A Privacy Preservation Model for RFID Data-Collections is Highly Secure and More Efficient than LKC-PrivacyProceedings of the 12th International Conference on Advances in Information Technology10.1145/3468784.3469853(1-11)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1145/3468784.3469853
Riyana SRiyana N(2021)Achieving Anonymization Constraints in High-Dimensional Data Publishing Based on Local and Global Data SuppressionsSN Computer Science10.1007/s42979-021-00936-73:1Online publication date: 23-Oct-2021
https://doi.org/10.1007/s42979-021-00936-7
Riyana SRiyana NSujinda W(2021)An Anatomization Model for Farmer Data CollectionsSN Computer Science10.1007/s42979-021-00740-32:5Online publication date: 23-Jun-2021
https://doi.org/10.1007/s42979-021-00740-3
Riyana SNanthachumphu SRiyana N(2020)Achieving Privacy Preservation Constraints in Missing-Value DatasetsSN Computer Science10.1007/s42979-020-00241-91:4Online publication date: 4-Jul-2020
https://doi.org/10.1007/s42979-020-00241-9
Harnsamut NNatwichai JRiyana S(2018)Privacy Preservation for Trajectory Data Publishing by Look-Up Table GeneralizationDatabases Theory and Applications10.1007/978-3-319-92013-9_2(15-27)Online publication date: 18-May-2018
https://doi.org/10.1007/978-3-319-92013-9_2
Gramaglia MFiore MTarable ABanchs A(2017)Preserving mobile subscriber privacy in open datasets of spatiotemporal trajectoriesIEEE INFOCOM 2017 - IEEE Conference on Computer Communications10.1109/INFOCOM.2017.8056979(1-9)Online publication date: May-2017
https://doi.org/10.1109/INFOCOM.2017.8056979
Harnsamut NNatwichai J(2017)Privacy Preservation for Trajectory Data Publishing and Heuristic ApproachAdvances in Network-Based Information Systems10.1007/978-3-319-65521-5_71(787-797)Online publication date: 24-Aug-2017
https://doi.org/10.1007/978-3-319-65521-5_71
Ghasemi Komishani EAbadi MDeldar F(2016)PPTDKnowledge-Based Systems10.1016/j.knosys.2015.11.00794:C(43-59)Online publication date: 15-Feb-2016
https://dl.acm.org/doi/10.1016/j.knosys.2015.11.007
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