Privacy-aware Character Pattern Matching over Outsourced Encrypted Data

Abstract

Providing a method to efficiently search into outsourced encrypted data, without forsaking strong privacy guarantees, is a pressing concern rising from the separation of data ownership and data management typical of cloud-based applications. While several existing solutions allow a client to look up the occurrences of a substring in an outsourced document collection, the practical application requirements in terms of privacy and efficiency call for the improvement of such solutions. In this work, we present a privacy-preserving substring search protocol with a polylogarithmic communication cost and a limited computational effort on the server side. The proposed protocol provides search pattern and access pattern privacy, for both exact string search and character-pattern search with wildcards. Its extension to a multi-user setting shows significant savings in terms of outsourced storage w.r.t. a baseline solution where the whole dataset is replicated. The performance figures of an optimized implementation of our protocol, searching into a remotely stored genomic dataset, validate the practicality of the approach exhibiting a data transfer of less than 50 kiB to execute a query over a document of 40 MiB, with execution times on client and server in the range of a few seconds and a few minutes, respectively.