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Updated: Jul 24, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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A Privacy-Preserving Framework Using Homomorphic Encryption for Smart Metering Systems.

Weiyan Xu1, Jack Sun1, Rachel Cardell-Oliver1

  • 1Department of Computer Science and Software Engineering, The University of Western Australia, Perth, WA 6009, Australia.

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|July 11, 2023
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Summary
This summary is machine-generated.

Smart metering systems (SMSs) generate sensitive data. This study introduces a privacy-preserving framework using homomorphic encryption (HE) and trust boundaries to protect customer data across various SMS applications.

Keywords:
homomorphic encryptionsmart metering systemtrust boundary

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Area of Science:

  • Data Privacy
  • Cybersecurity
  • Applied Cryptography

Background:

  • Smart metering systems (SMSs) collect granular consumption data, posing privacy risks through behavior recognition and absence detection.
  • Homomorphic encryption (HE) offers a solution for secure computation on encrypted data, crucial for privacy-preserving data analysis.
  • Existing HE solutions lack adaptability to diverse SMS application scenarios and trust boundary considerations.

Purpose of the Study:

  • To propose a novel privacy-preserving framework for smart metering systems (SMSs).
  • To integrate homomorphic encryption (HE) with the concept of trust boundaries for enhanced data protection.
  • To demonstrate the framework's feasibility and performance across various SMS scenarios.

Main Methods:

  • Developed a privacy-preserving framework implementing homomorphic encryption (HE) tailored to different SMS trust boundary scenarios.
  • Evaluated the framework's performance using summation and variance computations on encrypted data.
  • Set security parameters to achieve a 128-bit security level.

Main Results:

  • The proposed HE framework successfully protects customer privacy in SMS data across varying trust boundaries.
  • Performance evaluation showed computation times of 58,235 ms for summation and 127,423 ms for variance with 100 households.
  • The computational overhead was deemed acceptable within a cost-benefit analysis for privacy assurance.

Conclusions:

  • The HE-based framework provides a viable and systematic solution for privacy protection in smart metering systems.
  • The trust boundary concept effectively guides the design of adaptable privacy solutions for diverse SMS applications.
  • The balance between robust privacy protection and acceptable computational cost is achievable for practical SMS deployments.