Protecting the grid topology and user consumption patterns during state estimation in smart grids based on data obfuscation

Lakshminarayanan Nandakumar,Zekeriya Erkin,Gamze Tillem,Tamas Keviczky

doi:10.1186/s42162-019-0078-y

Lakshminarayanan Nandakumar, Zekeriya Erkin + Show 2 more

Open Access

https://doi.org/10.1186/s42162-019-0078-y

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Abstract

Smart grids promise a more reliable, efficient, economically viable, and environment-friendly electricity infrastructure for the future. State estimation in smart grids plays a pivotal role in system monitoring, reliable operation, automation, and grid stabilization. However, the power consumption data collected from the users during state estimation can be privacy-sensitive. Furthermore, the topology of the grid can be exploited by malicious entities during state estimation to launch attacks without getting detected. Motivated by the essence of a secure state estimation process, we consider a weighted-least-squares estimation carried out batch-wise at repeated intervals, where the resource-constrained clients utilize a malicious cloud for computation services. We propose a secure masking protocol based on data obfuscation that is computationally efficient and successfully verifiable in the presence of a malicious adversary. Simulation results show that the state estimates calculated from the original and obfuscated dataset are exactly the same while demonstrating a high level of obscurity between the original and the obfuscated dataset both in time and frequency domain.

Highlights

Smart grids are widely regarded as a key ingredient to reduce the effects of growing energy consumption and emission levels (Commission 2014b)
Our main objective is different from these work since we focus on the privacy concerns of state estimation in smart grids
In Liu et al (2011), the authors present a new class of attacks called false data injection attacks (FDI) against state estimation in smart grids and show that an attacker can exploit the configuration of a power network to successfully introduce arbitrary errors into the state variables while bypassing existing techniques for bad measurement detection

Summary

Introduction

Smart grids are widely regarded as a key ingredient to reduce the effects of growing energy consumption and emission levels (Commission 2014b). In Liu et al (2011), the authors present a new class of attacks called false data injection attacks (FDI) against state estimation in smart grids and show that an attacker can exploit the configuration of a power network to successfully introduce arbitrary errors into the state variables while bypassing existing techniques for bad measurement detection. Contrary to the above work in smart grid state estimation, we focus on protecting both the power consumption data of the users and the grid topology. We propose Obfuscate(.), the first batch-wise state estimation scheme in smart grids with the goal of protecting both the power consumption data of the consumers and the grid topology. In “Simulation results” section, we present the simulation results and we conclude the paper in “Conclusions and future work” section

Background information

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Findings

Conclusions and future work