Abstract
Abnormal electricity data, caused by electricity theft or meter failure, leads to the inaccuracy of aggregation results. These inaccurate results not only harm the interests of users but also affect the decision-making of the power system. However, the existing data aggregation schemes do not consider the impact of abnormal data. How to filter out abnormal data is a challenge. To solve this problem, in this study, we propose a lightweight and privacy-friendly data aggregation scheme against abnormal data, in which the valid data can correctly be aggregated but abnormal data will be filtered out during the aggregation process. This is more suitable for resource-limited smart meters, due to the adoption of lightweight matrix encryption. The automatic filtering of abnormal data without additional processes and the detection of abnormal data sources are where our protocol outperforms other schemes. Finally, a detailed security analysis shows that the proposed scheme can protect the privacy of users’ data. In addition, the results of extensive simulations demonstrate that the additional computation cost to filter the abnormal data is within the acceptable range, which shows that our proposed scheme is still very effective.
Highlights
With the application of electricity in our daily life becoming increasingly extensive, more factors need to be considered in the production decisions of the cloud server [1,2], such as how to maintain a balance between supply and demand when electricity usage changes dramatically [3]
We propose a lightweight and privacy-friendly data aggregation scheme against abnormal data by using lightweight matrix encryption
We propose a lightweight and privacy-friendly data aggregation scheme against abnormal data to solve the problem that the abnormal electricity usage data cannot be filtered out when it is encrypted
Summary
With the application of electricity in our daily life becoming increasingly extensive, more factors need to be considered in the production decisions of the cloud server [1,2], such as how to maintain a balance between supply and demand when electricity usage changes dramatically [3]. To obtain the real-time electricity demand of users, their electricity usage data should be measured, aggregated, and analyzed through advanced metering infrastructure [8,9]. It is a noteworthy problem of the smart grid that the abnormal electricity data, caused by electricity theft or meter failure, can lead to inaccurate aggregation results. We propose a lightweight and privacy-friendly data aggregation scheme against abnormal data by using lightweight matrix encryption It is suitable for smart meters with limited computing power, since no time-consuming computation operators are involved.
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