Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/146652
Title: Utility-driven k-anonymization of public transport user data
Authors: Bhati, Bhawani Shanker
Ivanchev, Jordan
Bojic, Iva
Datta, Anwitaman
Eckhoff, David
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Source: Bhati, B. S., Ivanchev, J., Bojic, I., Datta, A., & Eckhoff, D. (2021). Utility-driven k-anonymization of public transport user data. IEEE Access, 9, 23608-23623. doi:10.1109/ACCESS.2021.3055505
Journal: IEEE Access
Abstract: In this paper, we propose a k-anonymity approach that prioritizes the generalization of attributes based on their utility. We focus on transport data, which we consider a special case in which many or all attributes are quasi-identifiers (e.g., origin, destination, ride start time), as they allow correlation with easily observable auxiliary data. The novelty in our approach lies in introducing normalization techniques as well as distance and utility metrics that allow the consideration of not only numerical attributes but also categorical attributes by representing them in tree or graph form. The prioritization of the attributes in the generalization process is based on the attributes’ utility and can further be influenced by either automatically or manually assigned attribute weights. We evaluate and compare different options for all components of our mechanism as well as present an extensive performance evaluation of our approach using real-world data. Lastly, we show in which cases suppression of records can counter-intuitively lead to higher data utility.
URI: https://hdl.handle.net/10356/146652
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2021.3055505
Rights: © 2021 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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