Dynamic anonymisation techniques analogy for multiple releases of data

Preeti Gupta and Vishal Bhatnagar

International Journal of Data Mining, Modelling and Management, 2014, vol. 6, issue 3, 239-260

Abstract: Data publication has become important due to its inherent research and analysis value. Data is often published by the service provider in the anonymised form for achieving confidentiality. Most of the anonymised techniques generally considered for anonymisation are static in nature which considers only fixed one time data release. In dynamic environment where data keeps evolving with time, static techniques may result in poor data analysis or re-identification risk. In this paper, various dynamic anonymisation techniques for multiple releases of data have been analysed that can help the researchers or the service providers to decide the best technique for the underlying dynamic context depending on the criterion to be optimised.

Keywords: privacy preservation; confidentiality; dynamic anonymisation; m-invariance; multiple data releases; data security. (search for similar items in EconPapers)
Date: 2014
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