Fault-Tolerant Secure Data Aggregation Schemes in Smart Grids: Techniques, Design Challenges, and Future Trends

Secure data aggregation is an important process that enables a smart meter to perform efficiently and accurately. However, the fault tolerance and privacy of the user data are the most serious concerns in this process. While the security issues of Smart Grids are extensively studied, these two issues have been ignored so far. Therefore, in this paper, we present a comprehensive survey of fault-tolerant and differential privacy schemes for the Smart Gird. We selected papers from 2010 to 2021 and studied the schemes that are specifically related to fault tolerance and differential privacy. We divided all existing schemes based on the security properties, performance evaluation, and security attacks. We provide a comparative analysis for each scheme based on the cryptographic approach used. One of the drawbacks of existing surveys on the Smart Grid is that they have not discussed fault tolerance and differential privacy as a major area and consider them only as a part of privacy preservation schemes. On the basis of our work, we identified further research areas that can be explored

Analysis of Privacy-aware Data Sharing in Cyber-physical Energy Systems

In this thesis, we determine the key factors and correlations among the privacy, security, and utility requirements of grid networks to ensure effective inter-and intra-actions within physical layer equipment (e.g., distributed energy resources (DERs), intelligent electronic devices (IEDs), etc.). We have conducted a comprehensive analysis of the existing consensus mechanisms in blockchain-enabled smart grids while pointing out the potential research gaps. We develop a practical and effective consensus mechanism for a private and permissioned blockchain-enabled Supervisory control and data acquisition (SCADA) system. Moreover, we bridge a common and popular industrial control system (ICS) protocol, distributed network protocol 3 (DNP3) with the blockchain network to ensure smooth operation. In addition, we develop differential privacy (DP)-enabled strategies to achieve data security, privacy, and utility requirements of the power system network under an adversarial setting. Specifically, we aim to analyze and develop a provable correlation between privacy loss and other DP parameters considering the variations of attacks and their impacts along with DP constraints. This will enable modern power grid designers to develop, design, and employ DP-based fault-tolerant models in data-driven power grid operation and control. Furthermore, we conduct feasibility and quality-of-service (QoS) analysis of the DP mechanism and the grid to achieve certified robustness. Feasibility analysis of the privacy measure provides an assessment of the practicability of differential privacy in grid operation and warns the operators about the possible failures and incoming attacks on physical layer operations. QoS is analyzed in the power grid in terms of data accuracy, computational overhead, and resource utilization

The Influence of Differential Privacy on Short Term Electric Load Forecasting

There has been a large number of contributions on privacy-preserving smart metering with Differential Privacy, addressing questions from actual enforcement at the smart meter to billing at the energy provider. However, exploitation is mostly limited to application of cryptographic security means between smart meters and energy providers. We illustrate along the use case of privacy preserving load forecasting that Differential Privacy is indeed a valuable addition that unlocks novel information flows for optimization. We show that (i) there are large differences in utility along three selected forecasting methods, (ii) energy providers can enjoy good utility especially under the linear regression benchmark model, and (iii) households can participate in privacy preserving load forecasting with an individual re-identification risk < 60%, only 10% over random guessing.Comment: This is a pre-print of an article submitted to Springer Open Journal "Energy Informatics