Towards secure end-to-end data aggregation in AMI through delayed-integrity-verification

Keoh, S. L. and Tang, Z. (2014) Towards secure end-to-end data aggregation in AMI through delayed-integrity-verification. In: IEEE 10th International Conference on Information Assurrance and Security (IAS), Okinawa, Japan, 27 - 29 Nov 2014,

98751.pdf - Accepted Version


Publisher's URL:


The integrity and authenticity of the energy usage data in Advanced Metering Infrastructure (AMI) is crucial to ensure the correct energy load to facilitate generation, distribution and customer billing. Any malicious tampering to the data must be detected immediately. This paper introduces secure end-to-end data aggregation for AMI, a security protocol that allows the concentrators to securely aggregate the data collected from the smart meters, while enabling the utility back-end that receives the aggregated data to verify the integrity and data originality. Compromise of concentrators can be detected. The aggregated data is protected using Chameleon Signatures and then forwarded to the utility back-end for verification, accounting, and analysis. Using the Trapdoor Chameleon Hash Function, the smart meters can periodically send an evidence to the utility back-end, by computing an alternative message and a random value (m', r) such that m' consists of all previous energy usage measurements of the smart meter in a specified period of time. By verifying that the Chameleon Hash Value of (m', r) and that the energy usage matches those aggregated by the concentrators, the utility back-end is convinced of the integrity and authenticity of the data from the smart meters. Any data anomaly between smart meters and concentrators can be detected, thus indicating potential compromise of concentrators.

Item Type:Conference Proceedings
Additional Information:© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Glasgow Author(s) Enlighten ID:Keoh, Dr Sye Loong
Authors: Keoh, S. L., and Tang, Z.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2014 IEEE

University Staff: Request a correction | Enlighten Editors: Update this record