n-Dependency: dependency diversity in anatomised microdata tables

• Published in: Logic journal of the IGPL 2011-10, Vol.19 (5), p.679-702
• Main Authors: Landberg, Anders H, Rahayu, J. Wenny, Pardede, Eric
• Format: Article
• Language: English
• ISSN: 1367-0751; 1368-9894
• DOI: 10.1093/jigpal/jzq015

k-Anonymity and l-Diversity have laid the fundamental techniques for preserving privacy in microdata, and many research works have been inspired by them, proposing better and stronger levels of privacy. A common technique for achieving higher privacy in microdata tables is to diversify the records in such a way that sensitive information stored in the data is less likely to be disclosed. While most of the approaches succeed in protecting the original sensitive information to a high degree, issues arise when sensitive values are generalised along a hierarchical taxonomy, causing an increase in probability of privacy disclosure already after the first level of generalisation. This paper introduces n-Dependency, a novel technique that considers the hierarchical nature of sensitive information and their generalisations when diversifying the microdata. We propose a formal model and algorithms, and verify our technique by conducting extensive experiments.