Privacy-preserving data aggregation in smart metering systems

Privacy-preserving data aggregation in smart metering systems

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In this chapter, a survey of protocols for privacy-preserving data aggregation in smart metering systems is presented. They are necessary to protect customers'profiles from adversaries, who can predict customers' behaviour and manipulate them. The state of the art covers the entire cycle of a smart grid with real-time consolidated consumption, billing processes and verifications. However, the real-time consolidated consumption is public in the best protocol. In this work, we find an improved protocol that can hide real-time consolidated consumptions keeping them accessible only to the public utility. In addition, a complexity analysis of algorithms is presented and a simulation with millions of real-world measurements collected by thousands of smart meters is run to validate the theoretical evaluation. Furthermore, the improved protocol slightly outperforms the state of the art in the encryption algorithm, which runs in constrained smart meters. Moreover, such techniques can be applied in several other research areas.

Chapter Contents:

  • 2.1 Introduction
  • 2.2 Definitions
  • 2.2.1 List of acronyms
  • 2.2.2 List of symbols
  • 2.3 Background
  • 2.4 State-of-the-art protocols
  • 2.4.1 Homomorphic encryption
  • 2.4.2 Commitments
  • 2.4.3 Symmetric DC-Net (SDC-Net)
  • 2.4.4 Asymmetric DC-Net (ADC-Net)
  • 2.5 An improved ADC-Net
  • 2.6 Comparison with related work
  • 2.6.1 Privacy
  • 2.6.2 Communication
  • 2.6.3 Processing time
  • 2.6.4 Techniques
  • 2.7 Simulations
  • 2.7.1 Real-world data set
  • 2.7.2 Software and hardware
  • 2.7.3 Simulation parameters
  • 2.7.4 Simulation results
  • Encryption
  • Aggregation
  • Decryption
  • Overall processing time
  • 2.8 Conclusions
  • Acknowledgements
  • Bibliography

Inspec keywords: protocols; smart meters; customer profiles; data aggregation; power engineering computing; data privacy; public utilities

Other keywords: encryption algorithm; smart metering systems; public utility; complexity analysis; customer behaviour; privacy-preserving data aggregation; billing processes; customer profiles; protocols; smart grid

Subjects: Power system management, operation and economics; Data security; Power system measurement and metering; Power engineering computing; Protocols; Protocols

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