Smart grid allows fine-grained smart metering data collection which can improve the efficiency and reliability of the grid. Unfortunately, this vast collection of data also impose risks to users’ privacy. In this paper, we propose a novel protocol that allows suppliers and grid operators to collect users’ aggregate metering data in a secure and privacy-preserving manner. We use secure multiparty computation to ensure privacy protection. In addition, we propose three different data aggregation algorithms that offer different balances between privacy-protection and performance. Our protocol is designed for a realistic scenario in which the data need to be sent to different parties, such as grid operators and suppliers. Furthermore, it facilitates an accurate calculation of transmission, distribution and grid balancing fees in a privacy-preserving manner. We also present a security analysis and a performance evaluation of our protocol based on existing multiparty computation algorithms.

This paper provides a comprehensive security analysis of the Electric Vehicle (EV) charging service in Smart Grid (SG) environment (i.e. the “smart” EV charging application). It first describes three EV charging scenarios, at home, at work and at public places. Based on these use-case scenarios, the paper presents a model for smart EV charging, consisted of application entities and interactions among them. It then illustrates potential message types communicated among these entities. Based on this model and the exchanged messages, the paper analyses security problems and potential security threats imposed on the entities, which leads to the specification of a set of security and privacy requirements. These requirements could be used to guide the future design of solutions for secure smart EV charging systems and/or a risk/impact assessment of such systems.

This paper proposes a novel solution, called a decentralized, efficient, privacy-preserving, and selective aggregation (DEP2SA) scheme, designed to support secure and user privacy-preserving data collection in the advanced metering infrastructure. DEP2SA is more efficient and applicable in real-life deployment, as compared with the state of the art, by adopting and adapting a number of key technologies: 1) it uses a multi-recipient system model, making it more applicable to a liberalized electricity market; 2) it uses the homomorphic Paillier encryption and selective aggregation methods to protect users' consumption data against both external and internal attacks, thus making it more secure; 3) it aggregates data at the gateways that are closest to the data originator, thus saving bandwidth and reducing the risk of creating a performance bottleneck in the system; and 4) it uses short signature and batch signature verification methods to further reduce computational and communication overheads imposed on aggregating nodes. The scheme has been analyzed in terms of security, computational, and communication overheads, and the results show that it is more secure, efficient, and scalable than related schemes.

This paper proposes a local electricity trading market and provides a comprehensive security analysis of this market. It first presents a market for electricity trading among individual users, and describes the different entities and the interactions among them. Based on this market model and the interactions, the paper analyses security problems and potential privacy threats imposed on users, which leads to the specification of a set of security and privacy requirements. These requirements can be used to guide the future design of secure local electricity trading markets or to perform a risk assessment of such markets.