Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/3843
Title: A utility based approach for data stream anonymization
Authors: Sopaoğlu, Uğur
Abul, Osman
Keywords: Data streams
data anonymization
data privacy
clustering
Issue Date: Jun-2020
Publisher: Springer
Source: Sopaoglu, U., Abul, O. (2019). A utility based approach for data stream anonymization. Journal of Intelligent Information Systems, 1-27.
Abstract: Data streams are good models to characterize dynamic, on-line, fast and high-volume data requirements of today's businesses. However, sensitivity of data is usually an obstacle for deployment of many data streams applications. To address this challenging issue, many privacy preserving models, including k-anonymity, have been adapted to data streams. Data stream anonymization frameworks have already addressed how to preserve data quality as much as possible under bounded delays. In this work, our main motivation is to minimize average delay while keeping data quality high. It is our claim that data utility is a function of both data quality and data aging in data streams processing tasks. However, there is a tradeoff between data aging and data quality optimizations. To this end, we present a tunable data stream k-anonymization framework and an algorithm named UBDSA (Utility Based Approach for Data Stream Anonymization). To attain high quality anonymity groups, UBDSA also introduces a new distance metric, named CAIL (Cardinality Aware Information Loss). Our experimental evaluations compare performance of UBDSA with the literature, and the results show its merit in terms of better average delay and information loss.
URI: https://hdl.handle.net/20.500.11851/3843
https://link.springer.com/article/10.1007%2Fs10844-019-00577-6
ISSN: 0925-9902
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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