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Due to the openness of the vehicle-to-grid (V2G) network, the upload of charging and discharging data faces severe security challenges such as eavesdropping, tampering, and forgery. These challenges can lead to privacy breaches, transmission delays, and service quality degradation. To address these issues, a V2G network architecture based on cloud–fog-end is designed, and a charging and discharging data privacy protection scheme is proposed. We employ a pseudonym mechanism to achieve the conditional privacy protection of electric vehicle (EV) users. We design a certificateless aggregate signcryption (CLASC) algorithm to guarantee the security of uploading the charging and discharging privacy data. The algorithm solves certificate management and key escrow issues, utilizes aggregate signature operations to save network bandwidth, and avoids complex computations like bilinear pairings and exponents. Additionally, the scheme delegates the aggregate verification process to the fog layer, thereby alleviating the computational burden on the cloud layer, decreasing transmission delays, and enhancing the efficiency and reliability of the V2G network. The analysis results indicate that the scheme not only meets the required security objectives, but also has lower computational and communication overheads, making it suitable for scenarios involving the charging and discharging of large-scale EVs in V2G networks. [ABSTRACT FROM AUTHOR]

Due to the openness of the vehicle-to-grid (V2G) network, the upload of charging and discharging data faces severe security challenges such as eavesdropping, tampering, and forgery. These challenges can lead to privacy breaches, transmission delays, and service quality degradation. To address these issues, a V2G network architecture based on cloud–fog-end is designed, and a charging and discharging data privacy protection scheme is proposed. We employ a pseudonym mechanism to achieve the conditional privacy protection of electric vehicle (EV) users. We design a certificateless aggregate signcryption (CLASC) algorithm to guarantee the security of uploading the charging and discharging privacy data. The algorithm solves certificate management and key escrow issues, utilizes aggregate signature operations to save network bandwidth, and avoids complex computations like bilinear pairings and exponents. Additionally, the scheme delegates the aggregate verification process to the fog layer, thereby alleviating the computational burden on the cloud layer, decreasing transmission delays, and enhancing the efficiency and reliability of the V2G network. The analysis results indicate that the scheme not only meets the required security objectives, but also has lower computational and communication overheads, making it suitable for scenarios involving the charging and discharging of large-scale EVs in V2G networks.

In the V2G network, the release and sharing of real-time data are of great value for data mining. However, publishing these data directly to service providers may reveal the privacy of users. Therefore, it is necessary that the data release model with a privacy protection mechanism protects user privacy in the case of data utility. In this paper, we propose a privacy protection mechanism based on differential privacy to protect the release of data in V2G networks. To improve the utility of the data, we define a variable sliding window, which can dynamically and adaptively adjust the size according to the data. Besides, to allocate the privacy budget reasonably in the variable window, we consider the sampling interval and the proportion of the window. Through experimental analysis on real data sets, and comparison with two representative w event privacy protection methods, we prove that the method in this paper is superior to the existing schemes and improves the utility of the data.

In the V2G network, the release and sharing of real-time data are of great value for data mining. However, publishing these data directly to service providers may reveal the privacy of users. Therefore, it is necessary that the data release model with a privacy protection mechanism protects user privacy in the case of data utility. In this paper, we propose a privacy protection mechanism based on differential privacy to protect the release of data in V2G networks. To improve the utility of the data, we define a variable sliding window, which can dynamically and adaptively adjust the size according to the data. Besides, to allocate the privacy budget reasonably in the variable window, we consider the sampling interval and the proportion of the window. Through experimental analysis on real data sets, and comparison with two representative w event privacy protection methods, we prove that the method in this paper is superior to the existing schemes and improves the utility of the data., Competing Interests: Rixuan Qiu, Fuyong Zheng and Liang Liang are employed by State Grid Jiangxi Information & Telecommunication Company., (©2021 Qiu et al.)