We design and prototype protocols for processing smartmeter readings while preserving user privacy. We provide support for computing non-linear functions on encrypted readings, implemented by adapting to our setting efficient secret-sharing-based secure multi-party computation techniques. Meter readings are jointly processed by a (public) storage service and a few independent authorities, each owning an additive share of the readings. For non-linear processing, these parties consume pre-shared materials, produced by an off-line trusted third party. This party never processes private readings; it may be implemented using trusted hardware or somewhat homomorphic encryption. The protocol involves minimal, off-line support from the meters-a few keyed hash computations and no communication overhead.
In REF the authors propose a solution to preserve customers' privacy providing encrypted meter reading with the adoption of secret-sharing-based secure multi-party computation techniques.
Smart meter aggregation via secret-sharing
SEGS '13
Computer Science