Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

COAT: COnstraint-based anonymization of transactions

Loukides, Grigorios, Gkoulalas-Divanis, Aris and Malin, Bradley 2011. COAT: COnstraint-based anonymization of transactions. Knowledge and Information Systems 28 (2) , pp. 251-282. 10.1007/s10115-010-0354-4

Full text not available from this repository.

Abstract

Publishing transactional data about individuals in an anonymous form is increasingly required by organizations. Recent approaches ensure that potentially identifying information cannot be used to link published transactions to individuals’ identities. However, these approaches are inadequate to anonymize data that is both protected and practically useful in applications because they incorporate coarse privacy requirements, do not integrate utility requirements, and tend to explore a small portion of the solution space. In this paper, we propose the first approach for anonymizing transactional data under application-specific privacy and utility requirements. We model such requirements as constraints, investigate how these constraints can be specified, and propose COnstraint-based Anonymization of Transactions, an algorithm that anonymizes transactions using a flexible anonymization scheme to meet the specified constraints. Experiments with benchmark datasets verify that COAT significantly outperforms the current state-of-the-art algorithm in terms of data utility, while being comparable in terms of efficiency. Our approach is also shown to be effective in preserving both privacy and utility in a real-world scenario that requires disseminating patients’ information.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: Privacy-preserving data publication; Anonymity; Transactional data; Context-aware anonymization; Privacy constraints; Utility constraints
Additional Information: From the issue entitled "Special Issue on "Context-Aware Data Mining (CADM)""
Publisher: Springer
ISSN: 0219-1377
Last Modified: 12 Jun 2019 02:51
URI: http://orca.cf.ac.uk/id/eprint/14102

Citation Data

Cited 51 times in Google Scholar. View in Google Scholar

Cited 43 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item