EPIC: Efficient Privacy-Preserving Scheme with E2E Data Integrity and\n Authenticity for AMI Networks

In Advanced Metering Infrastructure (AMI) networks, smart meters should send\nfine-grained power consumption readings to electric utilities to perform\nreal-time monitoring and energy management. However, these readings can leak\nsensitive information about consumers' activities. Various privacy-preserving\nschemes for collecting fine-grained readings have been proposed for AMI\nnetworks. These schemes aggregate individual readings and send an aggregated\nreading to the utility, but they extensively use asymmetric-key cryptography\nwhich involves large computation/communication overhead. Furthermore, they do\nnot address End-to-End (E2E) data integrity, authenticity, and computing\nelectricity bills based on dynamic prices. In this paper, we propose EPIC, an\nefficient and privacy-preserving data collection scheme with E2E data integrity\nverification for AMI networks. Using efficient cryptographic operations, each\nmeter should send a masked reading to the utility such that all the masks are\ncanceled after aggregating all meters' masked readings, and thus the utility\ncan only obtain an aggregated reading to preserve consumers' privacy. The\nutility can verify the aggregated reading integrity without accessing the\nindividual readings to preserve privacy. It can also identify the attackers and\ncompute electricity bills efficiently by using the fine-grained readings\nwithout violating privacy. Furthermore, EPIC can resist collusion attacks in\nwhich the utility colludes with a relay node to extract the meters' readings. A\nformal proof, probabilistic analysis are used to evaluate the security of EPIC,\nand ns-3 is used to implement EPIC and evaluate the network performance. In\naddition, we compare EPIC to existing data collection schemes in terms of\noverhead and security/privacy features.\n