An approximate microaggregation approach for microdata protection
Article
Article Title | An approximate microaggregation approach for microdata protection |
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ERA Journal ID | 17852 |
Article Category | Article |
Authors | Sun, Xiaoxun (Author), Wang, Hua (Author), Li, Jiuyong (Author) and Zhang, Yanchun (Author) |
Journal Title | Expert Systems with Applications |
Journal Citation | 39 (2), pp. 2211-2219 |
Number of Pages | 9 |
Year | 2012 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 0957-4174 |
1873-6793 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.eswa.2011.04.223 |
Web Address (URL) | http://www.sciencedirect.com/science/article/pii/S0957417411007500 |
Abstract | Microdata protection is a hot topic in the field of Statistical Disclosure Control, which has gained special interest after the disclosure of 658,000 queries by the America Online (AOL) search engine in August 2006. Many algorithms, methods and properties have been proposed to deal with microdata disclosure. One of the emerging concepts in microdata protection is k-anonymity, introduced by Samarati and Sweeney. k-Anonymity provides a simple and efficient approach to protect private individual information and is gaining increasing popularity. k-Anonymity requires that every record in the microdata table released be indistinguishably related to no fewer than k respondents. In this paper, we apply the concept of entropy to propose a distance metric to evaluate the amount of mutual information among records in microdata, and propose a method of constructing dependency tree to find the key attributes, which we then use to process approximate microaggregation. Further, we adopt this new microaggregation technique to study k-anonymity problem, and an efficient algorithm is developed. Experimental results show that the proposed microaggregation technique is efficient and effective in the terms of running time and information loss. |
Keywords | privacy protection; data anonymization; microaggregation |
ANZSRC Field of Research 2020 | 460499. Cybersecurity and privacy not elsewhere classified |
460908. Information systems organisation and management | |
490103. Calculus of variations, mathematical aspects of systems theory and control theory | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Department of Mathematics and Computing |
University of South Australia | |
Victoria University | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q1823/an-approximate-microaggregation-approach-for-microdata-protection
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