DWE: decrypting learning with errors with errors

The Learning with Errors (LWE) problem is a novel foundation of a variety of cryptographic applications, including quantumly-secure public-key encryption, digital signature, and fully homomorphic encryption. In this work, we propose an approximate decryption technique for LWE-based cryptosystems. Based on the fact that the decryption process for such systems is inherently approximate, we apply hardware-based approximate computing techniques. Rigorous experiments have shown that the proposed technique simultaneously achieved 1.3x (resp., 2.5x) speed increase, 2.06x (resp., 7.89x) area reduction, 20.5% (resp., 4x) of power reduction, and an average of 27.1% (resp., 65.6%) ciphertext size reduction for public-key encryption scheme (resp., a state-of-the-art fully homomorphic encryption scheme).