Hardware acceleration of Private Information Retrieval protocols using GPUs

Abstract

Private Information Retrieval (PIR) protocols allow users to search for data items stored at an untrusted server, without disclosing to the server the search attributes. Several computational PIR protocols provide cryptographic-strength guarantees for the privacy of users, building upon well-known hard mathematical problems, such as factorisation of large integers. Unfortunately, the computational-intensive nature of these solutions results in significant performance overhead, preventing their adoption in practice. In this paper, we employ graphical processing units (GPUs) to speed up the cryptographic operations required by PIR. We identify the challenges that arise when using GPUs for PIR and we propose solutions to address them. To the best of our knowledge, this is the first work to use GPUs for efficient private information retrieval, and an important first step towards GPU-based acceleration of a broader range of secure data operations. Our experimental evaluation shows that GPUs improve performance by more than an order of magnitude.