Abstract:
As the Internet of Things (IoT) gets more pervasive, its areas of usage expands. Smart Metering systems
is such an IoT-enabled technology that enables convenient and high frequency data collection compared
to existing metering systems. However, such a frequent data collection puts the consumers’ privacy in
risk as it helps expose the consumers’ daily habits. Secure in-network data aggregation can be used
to both preserve consumers’ privacy and reduce the packet traffic due to high frequency metering
data. The privacy can be provided by performing the aggregation on concealed metering data. Fully
homomorphic encryption (FHE) and secure multiparty computation (secure MPC) are the systems that
enable performing multiple operations on concealed data. However, both FHE and secure MPC systems
have some overhead in terms of data size or message complexity. The overhead is compounded in the
IoT-enabled networks such as Smart Grid (SG) Advanced Metering Infrastructure (AMI). In this paper,
we propose new protocols to adapt FHE and secure MPC to be deployed in SG AMI networks that are
formed using wireless mesh networks. The proposed protocols conceal the smart meters’ (SMs) reading
data by encrypting it (FHE) or computing its shares on a randomly generated polynomial (secure MPC).
The encrypted data/computed shares are aggregated at some certain aggregator SM(s) up to the gateway
of the network in a hierarchical manner without revealing the readings’ actual value. To assess their
performance, we conducted extensive experiments using the ns-3 network simulator. The simulation
results indicate that the secure MPC-based protocol can be a viable privacy-preserving data aggregation
mechanism since it not only reduces the overhead with respect to FHE but also almost matches the
performance of the Paillier cryptosystem when it is used within a proper sized AMI network.
