Security and Privacy in Smart Grid

Smart grid utilizes different communication technologies to enhance the reliability and efficiency of the power grid; it allows bi-directional flow of electricity and information, about grid status and customers requirements, among different parties in the grid, i.e., connect generation, distribution, transmission, and consumption subsystems together. Thus, smart grid reduces the power losses and increases the efficiency of electricity generation and distribution. Although smart grid improves the quality of grid's services, it exposes the grid to the cyber security threats that communication networks suffer from in addition to other novel threats because of power grid's nature. For instance, the electricity consumption messages sent from consumers to the utility company via wireless network may be captured, modified, or replayed by adversaries. As a consequent, security and privacy concerns are significant challenges in smart grid. Smart grid upgrade creates three main communication architectures: The first one is the communication between electricity customers and utility companies via various networks; i.e., home area networks (HANs), building area networks (BANs), and neighbour area networks (NANs), we refer to these networks as customer-side networks in our thesis. The second architecture is the communication between EVs and grid to charge/discharge their batteries via vehicle-to-grid (V2G) connection. The last network is the grid's connection with measurements units that spread all over the grid to monitor its status and send periodic reports to the main control center (CC) for state estimation and bad data detection purposes. This thesis addresses the security concerns for the three communication architectures. For customer-side networks, the privacy of consumers is the central concern for these networks; also, the transmitted messages integrity and confidentiality should be guaranteed. While the main security concerns for V2G networks are the privacy of vehicle's owners besides the authenticity of participated parties. In the grid's connection with measurements units, integrity attacks, such as false data injection (FDI) attacks, target the measurements' integrity and consequently mislead the main CC to make the wrong decisions for the grid. The thesis presents two solutions for the security problems in the first architecture; i.e., the customer-side networks. The first proposed solution is security and privacy-preserving scheme in BAN, which is a cluster of HANs. The proposed scheme is based on forecasting the future electricity demand for the whole BAN cluster. Thus, BAN connects to the electricity provider only if the total demand of the cluster is changed. The proposed scheme employs the lattice-based public key NTRU crypto-system to guarantee the confidentiality and authenticity of the exchanged messages and to further reduce the computation and communication load. The security analysis shows that our proposed scheme can achieve the privacy and security requirements. In addition, it efficiently reduces the communication and computation overhead. According to the second solution, it is lightweight privacy-preserving aggregation scheme that permits the smart household appliances to aggregate their readings without involving the connected smart meter. The scheme deploys a lightweight lattice-based homomorphic crypto-system that depends on simple addition and multiplication operations. Therefore, the proposed scheme guarantees the customers' privacy and message integrity with lightweight overhead. In addition, the thesis proposes lightweight secure and privacy-preserving V2G connection scheme, in which the power grid assures the confidentiality and integrity of exchanged information during (dis)charging electricity sessions and overcomes EVs' authentication problem. The proposed scheme guarantees the financial profits of the grid and prevents EVs from acting maliciously. Meanwhile, EVs preserve their private information by generating their own pseudonym identities. In addition, the scheme keeps the accountability for the electricity-exchange trade. Furthermore, the proposed scheme provides these security requirements by lightweight overhead; as it diminishes the number of exchanged messages during (dis)charging sessions. Simulation results demonstrate that the proposed scheme significantly reduces the total communication and computation load for V2G connection especially for EVs. FDI attack, which is one of the severe attacks that threatens the smart grid's efficiency and reliability, inserts fake measurements among the correct ones to mislead CC to make wrong decisions and consequently impact on the grid's performance. In the thesis, we have proposed an FDI attack prevention technique that protects the integrity and availability of the measurements at measurement units and during their transmission to the CC, even with the existence of compromised units. The proposed scheme alleviates the negative impacts of FDI attack on grid's performance. Security analysis and performance evaluation show that our scheme guarantees the integrity and availability of the measurements with lightweight overhead, especially on the restricted-capabilities measurement units. The proposed schemes are promising solutions for the security and privacy problems of the three main communication networks in smart grid. The novelty of these proposed schemes does not only because they are robust and efficient security solutions, but also due to their lightweight communication and computation overhead, which qualify them to be applicable on limited-capability devices in the grid. So, this work is considered important progress toward more reliable and authentic smart grid

An efficient privacy-preserving authentication scheme for energy internet-based vehicle-to-grid communication

The energy Internet (EI) represents a new electric grid infrastructure that uses computing and communication to transform legacy power grids into systems that support open innovation. EI provides bidirectional communication for analysis and improvement of energy usage between service providers and customers. To ensure a secure, reliable, and efficient operation, the EI should be protected from cyber attacks. Thus, secure and efficient key establishment is an important issue for this Internet-based smart grid environment. In this paper, we propose an efficient privacy-preserving authentication scheme for EI-based vehicle-to-grid communication using lightweight cryptographic primitives such as one-way non-collision hash functions. In our proposed scheme, a customer can securely access services provided by the service provider using a symmetric key established between them. Detailed security and performance analysis of our proposed scheme are presented to show that it is resilient against many security attacks, cost effective in computation and communication, and provides an efficient solution for the EI

Security Challenges in Smart-Grid Metering and Control Systems

The smart grid is a next-generation power system that is increasingly attracting the attention of government, industry, and academia. It is an upgraded electricity network that depends on two-way digital communications between supplier and consumer that in turn give support to intelligent metering and monitoring systems. Considering that energy utilities play an increasingly important role in our daily life, smart-grid technology introduces new security challenges that must be addressed. Deploying a smart grid without adequate security might result in serious consequences such as grid instability, utility fraud, and loss of user information and energy-consumption data. Due to the heterogeneous communication architecture of smart grids, it is quite a challenge to design sophisticated and robust security mechanisms that can be easily deployed to protect communications among different layers of the smart grid-infrastructure. In this article, we focus on the communication-security aspect of a smart-grid metering and control system from the perspective of cryptographic techniques, and we discuss different mechanisms to enhance cybersecurity of the emerging smart grid. We aim to provide a comprehensive vulnerability analysis as well as novel insights on the cybersecurity of a smart grid

A Survey on Cryptography Key Management Schemes for Smart Grid

A Smart grid is a modern electricity delivery system. It is an integration of energy systems and other necessary elements including traditional upgrades and new grid technologies with renewable generation and increased consumer storage. It uses information and communication technology (ICT) to operate, monitor and control data between the generation source and the end user. Smart grids have duplex power flow and communication to achieve high efficiency, reliability, environmental, economics, security and safety standards. However, along with unique facilities, smart grids face security challenges such as access control, connectivity, fault tolerance, privacy, and other security issues. Cyber-attacks, in the recent past, on critical infrastructure including smart grids have highlighted security as a major requirement for smart grids. Therefore, cryptography and key management are necessary for smart grids to become secure and realizable. Key management schemes are processes of key organizational frameworks, distribution, generation, refresh and key storage policies. Currently, several secure schemes, related to key management for smart grid have been proposed to achieve end-to-end secure communication. This paper presents a comprehensive survey and discussion on the current state of the key management of smart grids

An efficient data aggregation scheme for privacy-friendly dynamic pricing-based billing and demand-response management in smart grids

Smart grids take advantage of information and communication technologies to achieve energy efficiency, automation and reliability. These systems allow two-way communications and power flow between the grid and consumers. However, these bidirectional communications introduce several security and privacy threats to consumers. One of the open challenges in this context is user privacy when smart meters are used to capture fine-grained energy usage information. Although considerable research has been carried out in this direction, most of the existing solutions invariably introduce computational complexity and overhead, which makes them infeasible for resource constrained smart meters. In this paper, we propose a privacy-friendly and efficient data aggregation scheme (EDAS) for dynamic pricing based billing and demand-response management in smart grids. To the best of our knowledge, this is the first paper to address privacy in the context of billing under dynamic electricity pricing. Security and performance analyses show that the proposed scheme offers better privacy protection for electric meter reading aggregation and computational efficiency, as compared to existing schemes

Lightweight and privacy-friendly spatial data aggregation for secure power supply and demand management in smart grids

The concept of smart metering allows real-time measurement of power demand which in turn is expected to result in more efficient energy use and better load balancing. However, finely granular measurements reported by smart meters can lead to starkly increased exposure of sensitive information, including various personal attributes and activities. Even though several security solutions have been proposed in recent years to address this issue, most of the existing solutions are based on publickey cryptographic primitives such as homomorphic encryption, elliptic curve digital signature algorithms (ECDSA), etc. which are ill-suited for the resource constrained smart meters. On the other hand, to address the computational inefficiency issue, some masking-based solutions have been proposed. However, these schemes cannot ensure some of the imperative security properties such as consumer’s privacy, sender authentication, etc. In this paper, we first propose a lightweight and privacyfriendly masking-based spatial data aggregation scheme for secure forecasting of power demand in smart grids. Our scheme only uses lightweight cryptographic primitives such as hash functions, exclusive-OR operations, etc. Subsequently, we propose a secure billing solution for smart grids. As compared to existing solutions, our scheme is simple and can ensure better privacy protection and computational efficiency, which are essential for smart grids