We propose a privacy-preserving aggregation scheme under a malicious attacks model, in which the aggregator may forge householders’ billing, or a neighborhood aggregation data, or collude with compromised smart meters to reveal object householders’ fine-grained data. The scheme can generate spatially total consumption in a neighborhood at a timestamp and temporally a householder’s billing in a series of timestamps. The proposed encryption scheme of imposing masking keys from pseudo-random function (PRF) between pairwise nodes on partitioned data ensures the confidentiality of individual fine-grained data, and fends off the power theft of n
-2 smart meters at most (n
is the group size of smart meters in a neighborhood). Compared with the afore-mentioned methods of public key encryption in most related literatures, the simple and lightweight combination of PRF with modular addition not only is customized to the specific needs of smart grid, but also facilitates any node’s verification for local aggregation or global aggregation with low cost overhead. The publicly verifiable scenarios are very important for self-sufficient, remote places, which can only afford renewable energy and can manage its own energy price according to the energy consumption circumstance in a neighborhood.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited