Secure aggregation lets a server learn the sum of inputs from multiple users without learning individual contributions. Recent single-server protocols achieve this with key- and message-additive homomorphic encryption (KAHE), but existing instantiations rely on lattice assumptions. We instantiate a KAHE from the Learning Parity with Noise (LPN) assumption and analyze the challenges that arise with the Hamming metric. Decryption of the aggregate amounts to decoding over a q-ary symmetric channel whose crossover probability grows with the number of users. Security under leakage of the key sum reduces to LPN with a noise rate that is quadratic in the KAHE noise rate, and a matching attack shows that this loss is inherent when all but two users collude. Asymptotically, we characterize the optimal communication cost in closed form, showing that the overhead over the raw payload vanishes as the input length grows, and decouple the field size from the input range via the Chinese remainder theorem. In cross-silo settings, our protocol requires less communication than information-theoretically secure aggregation for moderate to high collusion.

翻译：暂无翻译