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

Abstract

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.

Research on Power Data Security Classification Based on O-Svm Algorithm

“…Therefore, the feature subset selected by using CHI-MI-P has better differentiability than the complete set of highdimensional features, which can accelerate the convergence speed of O-SVM. The word frequency calculation parameter and word frequency weight parameter are introduced for the mutual information, as shown in equation (1).…”

“…With the rapid development of information technology, the power industry ushered in the era of big data. As a critical information infrastructure operating unit, electric power companies have a huge amount of data, which contains a large amount of user privacy information, and the security protection of these sensitive data is particularly important [1] . In the application process of big data, the principle of security and development must always be adhered to in order to ensure that the value of the data is fully utilized while solving the problems of data security and personal information protection [2] .…”