Frequent grams based embedding for privacy preserving record linkage
Luca Bonomi, Li Ping Xiong, Rui Chen, Benjamin C. M. Fung · 2012
In this paper, we study the problem of privacy preserving record linkage which aims to perform record linkage without revealing anything about the non-linked records. We propose a new secure embedding strategy based on frequent variable length grams which allows record linkage on the embedded space. The frequent grams used for constructing the embedding base are mined from the original database under the framework of differential privacy. Compared with the state-of-the-art secure matching schema [15], our approach provides formal, provable privacy guarantees and achieves better scalability while providing comparable utility.