Traditional electricity meters are replaced by Smart Meters in customers' households. Smart Meters collects fine-grained utility consumption profiles from customers, which in turn enables the introduction of dynamic, time-of-use tariffs. However, the fine-grained usage data that is compiled in this process also allows to infer the inhabitant's personal schedules and habits. We propose a privacy-preserving protocol that enables billing with time-of-use tariffs without disclosing the actual consumption profile to the supplier. Our approach relies on a zero-knowledge proof based on Pedersen Commitments performed by a plug-in privacy component that is put into the communication link between Smart Meter and supplier's back-end system. We require no changes to the Smart Meter hardware and only small changes to the software of Smart Meter and back-end system. In this paper we describe the functional and privacy requirements, the specification and security proof of our solution and give a performance evaluation of a prototypical implementation.
In @cite_6 a privacy-preserving detection algorithm for leakages in electricity distribution has been proposed. By aggregation across several Smart Meters the developed algorithm protects individual meter readings while allowing grid operators to detect illegitimate unknown load. Their approach does not allow individual billing, yet this is the main application of our paper.
@cite_6
2096219879
The first part of this paper discusses developments wrt. smart (electricity) meters (simply called E-meters) in general, with emphasis on security and privacy issues. The second part will be more technical and describes protocols for secure communication with E-meters and for fraud detection (leakage) in a privacy-preserving manner. Our approach uses a combination of Paillier's additive homomorphic encryption and additive secret sharing to compute the aggregated energy consumption of a given set of users.