As smart grids are getting popular and being widely implemented, preserving the privacy of consumers is becoming more substantial. Power generation and pricing in smart grids depends on the continuously gathered information from the consumers. However, having access to the data relevant to the electricity consumption of each individual consumer is in conflict with its privacy. One common approach for preserving privacy is to aggregate data of different consumers and to use their smart-meters for calculating the bills. But in this approach, malicious consumers who send erroneous data to take advantage or disrupt smart grid cannot be identified. In this paper, we propose a new statistical-based scheme for data gathering and billing in which the privacy of consumers is preserved, and at the same time, if any consumer with erroneous data can be detected. Our simulation results verify these matters.
Along with the development of information technology, the traditional electrical grid is moving to smart grid technology. By using the smart grid, the users and utility providers can more efficiently manage and generate power. Along with the advantages, the smart grid is also faced with new security concerns. In the smart grid, the user's citizen identity information should be preserved and the offensive user should be traced. For some low-capacity devices, it is indispensable to perform complicated computation by using outsourcing computation. The authors provide the outsourcing computation through public cloud. Anonymity and traceability are two important security properties in the smart grid. They are the unity of opposites. On the basis of the security requirements, they propose the balanced anonymity and traceability for outsourcing small-scale data linear aggregation (BAT-LA) in the smart grid. The formal definition, system model and security model are presented. Then, a concrete BAT-LA protocol is designed by using the elliptic curve cryptography and proxy re-encryption. Through security analysis and performance analysis, the designed BAT-LA protocol is provably secure and efficient. The widespread deployment of Automatic Metering Infrastructures in Smart Grid scenarios rises great concerns about privacy preservation of user-related data, from which detailed information about customer's habits and behaviors can be deduced. Therefore, the users' individual measurements should be aggregated before being provided to External Entities such as utilities, grid managers and third parties. This paper proposes a security architecture for distributed aggregation of additive data, in particular energy consumption metering data, relying on Gateways placed at the customers' premises, which collect the data generated by local Meters and provide communication and cryptographic capabilities. The Gateways communicate with one another and with the External Entities by means of a public data network. We propose a secure communication protocol aimed at preventing Gateways and External Entities from inferring information about individual data, in which privacy-preserving aggregation is performed by means of a cryptographic homomorphic scheme. The routing of information flows can be centralized or it can be performed in a distributed fashion using a protocol inspired by Chord. We compare the performance of both approaches to the optimal solution minimizing the data aggregation delay. In vehicle-to-grid (V2G) networks, service providers are battery-powered vehicles, and the service consumer is the power grid. Security and privacy concerns are major obstacles for V2G networks to be extensively deployed. In 2011, proposed a very interesting privacy-preserving communication and precise reward architecture for V2G networks in smart grids. In this paper, we enhance ’s framework with the formal definitions of unforgeability and restrictiveness. Then, we propose a new traceable privacy-preserving communication and precise reward scheme with available cryptographic primitives. The proposed scheme is formally proven secure with well-established assumptions in the random oracle model. Thorough theoretical and experimental analyses demonstrate that our scheme is efficient and practical for secure V2G networks in smart grids.