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http://dx.doi.org/10.13089/JKIISC.2017.27.6.1519

A Study on a Differentially Private Model for Financial Data  

Kim, Hyun-il (Kongju National University)
Park, Cheolhee (Kongju National University)
Hong, Dowon (Kongju National University)
Choi, Daeseon (Kongju National University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.27, no.6, 2017 , pp. 1519-1534 More about this Journal
Abstract
Data de-identification is the one of the technique that preserves individual data privacy and provides useful information of data to the analyst. However, original de-identification techniques like k-anonymity have vulnerabilities to background knowledge attacks. On the contrary, differential privacy has a lot of researches and studies within several years because it has both strong privacy preserving and useful utility. In this paper, we analyze various models based on differential privacy and formalize a differentially private model on financial data. As a result, we can formalize a differentially private model on financial data and show that it has both security guarantees and good usefulness.
Keywords
De-identification; Differential privacy; Financial data;
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