Privacy preserving computation by fragmenting individual bits and distributing gates

Abstract

Solutions that allow the computation of arbitrary operations over data securely in the cloud are currently impractical. The holy grail of cryptography, fully homomorphic encryption, still requires minutes to compute a single operation. In order to provide a practical solution, this paper proposes taking a different approach to the problem of securely processing data. FRagmenting Individual Bits (FRIBs), a scheme which preserves user privacy by distributing bit fragments across many locations, is presented. Privacy is maintained by each server only receiving a small portion of the actual data, and solving for the rest results in a vast number of possibilities. Functions are defined with NAND logic gates, and are computed quickly as the performance overhead is shifted from computation to network latency. This paper details our proof of concept addition algorithm which took 346ms to add two 32-bit values-paving the way towards further improvements to get computations completed under 100ms.