Private Substring Search on Homomorphically Encrypted Data

With the rapid development of cloud storage services and IoT environment, how to securely and efficiently search without compromising privacy has been an indispensable problem. In order to address such a problem, much works have been proposed for searching over encrypted data. Motivated by storing sensitive data such as genomic and medical data, substring search for encrypted data has been studied. Previous work either leaks query access pattern using vulnerable cryptographic model or performs search over plaintext data by an encrypted query. Thus they are not compatible with outsourcing scenario where searched data is stored in encrypted form which is searched by an encrypted substring query without leaking query access pattern, i.e., private substring search. In order to perform private substring search, Fully Homomorphic Encryption (FHE) can be adopted although it induces computationally huge overhead. Because of the huge overhead, performing private substring search efficiently over FHE is a challenging task. In this work, we propose a private substring search protocol over encrypted data by adopting FHE followed by examining its feasibility. In particular, we make use of batching technique which can accelerate homomorphic computation in SIMD manner. In addition, we propose a data structure which can be useful to specific searching function for batched computation. Our experimental result showed our proposed method is feasible.