Similarity based interactive private information retrieval

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Abstract

Private Information Retrieval (PIR) schemes address users’ privacy concerns while querying public databases. Two major advancements that are needed for designing practical privacy preserving applications are: (i) constant communication complexity and (ii) private retrieval of matching documents. In this paper, we propose a new family of interactive schemes namely SIMPIR, that allow participating servers to interact with each other. Our methods are similarity based (i.e. the results could contain false positives but do not contain any false negatives). Importantly our approach has constant communication complexity agnostic of the size of database which is major improvement from known schemes. We achieve these results by slightly relaxing the traditional requirements of PIR schemes.

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Dara, S., & Muralidhara, V. N. (2017). Similarity based interactive private information retrieval. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10662 LNCS, pp. 151–169). Springer Verlag. https://doi.org/10.1007/978-3-319-71501-8_9

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