A generic private information retrieval scheme with parallel multi-exponentiations on multicore processors

Private Information Retrieval (PIR) enables the data owners to share and/or retrieve data on remote repositories without leaking any information as to which a data item is requested. Although it is always possible to download the entire dataset, this is clearly a waste of bandwidth. A fundamental approach in the literature for PIR is exploiting homomorphic cryptosystems. In these approaches, not one but many modular exponentiations need to be computed and multiplied to obtain the desired result. This multi‐exponentiation operation can be implemented by exponentiating the bases to their corresponding exponents one‐by‐one. However, when the operation is considered as a whole, it can be performed in a more efficient way. Although individual exponentiations are pleasingly parallelizable, the combined multi‐exponentiation requires a careful parallel implementation. In this work, we propose a generic tensor‐based PIR scheme and efficient and novel techniques to parallelize multi‐exponentiations on multicore processors with perfect load balance. The experimental results show that our load balancing techniques make a parallel multi‐exponentiation up to %27 faster when the size of the bases and the exponents are 4096 bits and the number of threads is 16