A big data anonymous batch verification scheme with conditional privacy preservation for power injection over vehicular network and 5G smart grid slice

Abstract

Abstract Internet of Things (IoT) is a new paradigm that has changed the way we live in our society by providing many intelligent applications such as smart healthcare, precision agriculture, smart city, smart supply chain, smart home, smart grid, and intelligent transportation. As an integration of smart grid and intelligent transportation, vehicle-to-grid (V2G) technology can make the power grid to communicate with the plugin electric vehicles (EVs), allowing the EVs to store greenpower energy from renewable energy sources and inject overplus power back to the power grid during the peak demand hours for financial gains. Nevertheless, security of transmitted information and users’ privacy preservation are very crucial to ensure fairness in the energy market and enhance users’ acceptability of this propitious technology. For instance, there is need to expeditiously authenticate massive power bids injected by EVs without exposing the owners’ private information. Therefore, a big data anonymous batch verification for injection of power over vehicular network and 5G smart grid slice based on a new ultraefficient certificateless aggregate signature (CL-AS) algorithm is proposed. The proposed scheme achieves batch-verifiable authentication of all the injected bids in an anonymous manner without compromising the privacy of participants. Moreover, we prove that the scheme is secure, assuming the Discrete Logarithm Problem (DLP) is intractable. The performance evaluation demonstrates its superiority in terms of efficiency over the related schemes.