An Efficient Authentication Protocol for Smart Grid Communication Based on On-Chip-Error-Correcting Physical Unclonable Function

Security has become a main concern for the smart grid to move from research and development to industry. The concept of security has usually referred to resistance to threats by an active or passive attacker. However, since smart meters (SMs) are often placed in unprotected areas, physical security has become one of the important security goals in the smart grid. Physical unclonable functions (PUFs) have been largely utilized for ensuring physical security in recent years, though their reliability has remained a major problem to be practically used in cryptographic applications. Although fuzzy extractors have been considered as a solution to solve the reliability problem of PUFs, they put a considerable computational cost to the resource-constrained SMs. To that end, we first propose an on-chip-error-correcting (OCEC) PUF that efficiently generates stable digits for the authentication process. Afterward, we introduce a lightweight authentication protocol between the SMs and neighborhood gateway (NG) based on the proposed PUF. The provable security analysis shows that not only the proposed protocol can stand secure in the Canetti-Krawczyk (CK) adversary model but also provides additional security features. Also, the performance evaluation demonstrates the significant improvement of the proposed scheme in comparison with the state-of-the-art

A Comprehensive Survey on the Cyber-Security of Smart Grids: Cyber-Attacks, Detection, Countermeasure Techniques, and Future Directions

One of the significant challenges that smart grid networks face is cyber-security. Several studies have been conducted to highlight those security challenges. However, the majority of these surveys classify attacks based on the security requirements, confidentiality, integrity, and availability, without taking into consideration the accountability requirement. In addition, some of these surveys focused on the Transmission Control Protocol/Internet Protocol (TCP/IP) model, which does not differentiate between the application, session, and presentation and the data link and physical layers of the Open System Interconnection (OSI) model. In this survey paper, we provide a classification of attacks based on the OSI model and discuss in more detail the cyber-attacks that can target the different layers of smart grid networks communication. We also propose new classifications for the detection and countermeasure techniques and describe existing techniques under each category. Finally, we discuss challenges and future research directions

Real-Time Machine Learning Models To Detect Cyber And Physical Anomalies In Power Systems

A Smart Grid is a cyber-physical system (CPS) that tightly integrates computation and networking with physical processes to provide reliable two-way communication between electricity companies and customers. However, the grid availability and integrity are constantly threatened by both physical faults and cyber-attacks which may have a detrimental socio-economic impact. The frequency of the faults and attacks is increasing every year due to the extreme weather events and strong reliance on the open internet architecture that is vulnerable to cyber-attacks. In May 2021, for instance, Colonial Pipeline, one of the largest pipeline operators in the U.S., transports refined gasoline and jet fuel from Texas up the East Coast to New York was forced to shut down after being attacked by ransomware, causing prices to rise at gasoline pumps across the country. Enhancing situational awareness within the grid can alleviate these risks and avoid their adverse consequences. As part of this process, the phasor measurement units (PMU) are among the suitable assets since they collect time-synchronized measurements of grid status (30-120 samples/s), enabling the operators to react rapidly to potential anomalies. However, it is still challenging to process and analyze the open-ended source of PMU data as there are more than 2500 PMU distributed across the U.S. and Canada, where each of which generates more than 1.5 TB/month of streamed data. Further, the offline machine learning algorithms cannot be used in this scenario, as they require loading and scanning the entire dataset before processing. The ultimate objective of this dissertation is to develop early detection of cyber and physical anomalies in a real-time streaming environment setting by mining multi-variate large-scale synchrophasor data. To accomplish this objective, we start by investigating the cyber and physical anomalies, analyzing their impact, and critically reviewing the current detection approaches. Then, multiple machine learning models were designed to identify physical and cyber anomalies; the first one is an artificial neural network-based approach for detecting the False Data Injection (FDI) attack. This attack was specifically selected as it poses a serious risk to the integrity and availability of the grid; Secondly, we extend this approach by developing a Random Forest Regressor-based model which not only detects anomalies, but also identifies their location and duration; Lastly, we develop a real-time hoeffding tree-based model for detecting anomalies in steaming networks, and explicitly handling concept drifts. These models have been tested and the experimental results confirmed their superiority over the state-of-the-art models in terms of detection accuracy, false-positive rate, and processing time, making them potential candidates for strengthening the grid\u27s security

Analisis Kestabilan Transient untuk Sistem Smart Grid Berdasarkan Metode Lintasan Kritis yang Mempertimbangkan Algoritma Persamaan Simultan

Kestabilan transient terjadi kerena ada gangguan besar pada sistem yang mempengaruhi generator. Gangguan akan menyebabkan masalah pada kestabilan sudut rotor generator. Hal ini sangat berbahaya bagi generator dan kestabilan sistem. Sistem yang dianalisis adalah sistem dengan beberapa generator. Saat terjadi gangguan, generator yang terkena pengaruh paling besar yang akan dianalisis atau disebut generator kritis. Karena analisis hanya dilakukan pada satu generator proses perhitungan akan lebih cepat. Penelitian ini menggunakan metode metode Lintasan Kritis (critical trajectory) dimana analisis dilakukan menggunakan lintasan yang menggambarkan hubungan antara sudut rotor dan kecepatan putar generator. Lintasan ini juga menggambarkan keadaan saat sistem berada dalam kondisi stabil, tidak stabil dan kritis. Hasil akhir dari metode ini adalah Critical Clearing Time (CCT) atau waktu maksimal yang diizinkan saat terjadi gangguan sebelum sistem kehilangan kestabilan. Pengujian dilakukan pada beberapa sistem untuk menguji keefektifan metode. Sistem yang digunakan adalah sistem loop dan radial yang menggunakan single circuit. Sistem juga diuji pada sistem konvensional dan smart grid. Hasil simulasi menunjukkan bahwa nilai CCT yang didapat dari metode critical trajectory akurat dan waktu perhitungannya cepat. ============================================================================================= Transient stability occurs because there is a big disturbance on the system that affecting generator. Interference will cause problems to the stability of the generator rotor angle. This is very dangerous for the generator and stability of the system. The system analyzed is a system with several generators. When fault occure, the most influenced generator is analyzed and this generator called a critical generator. Because the analysis is only done on one generator the calculation process can be faster. This research used critical trajectory method where analysis is done using a trajectory that describes the relationship between rotor angle and angular velocity of generator. This trajectory also describes the situation when the system is stable, unstable and critical condition. The end process of this method is Critical Clearing Time (CCT) or the maximum time allowed during interruption before the system loses stability. Testing is finished on several systems to prove the effectiveness of the method. The system was tested on loop and radial system that use a single circuit. This method has been tried on konventional system and smart grid as well. The simulation result shows that the CCT value obtained from critical trajectory method is accurate and the time of calculation is fast

Advances and Technologies in High Voltage Power Systems Operation, Control, Protection and Security

The electrical demands in several countries around the world are increasing due to the huge energy requirements of prosperous economies and the human activities of modern life. In order to economically transfer electrical powers from the generation side to the demand side, these powers need to be transferred at high-voltage levels through suitable transmission systems and power substations. To this end, high-voltage transmission systems and power substations are in demand. Actually, they are at the heart of interconnected power systems, in which any faults might lead to unsuitable consequences, abnormal operation situations, security issues, and even power cuts and blackouts. In order to cope with the ever-increasing operation and control complexity and security in interconnected high-voltage power systems, new architectures, concepts, algorithms, and procedures are essential. This book aims to encourage researchers to address the technical issues and research gaps in high-voltage transmission systems and power substations in modern energy systems

Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

Smart grid (SG) networks are newly upgraded networks of connected objects that greatly improve reliability, efficiency and sustainability of the traditional energy infrastructure. In this respect, the smart metering infrastructure (SMI) plays an important role in controlling, monitoring and managing multiple domains in the SG. Despite the salient features of SMI, security and privacy issues have been under debate because of the large number of heterogeneous devices that are anticipated to be coordinated through public communication networks. This survey paper shows a brief overview of real cyber attack incidents in traditional energy networks and those targeting the smart metering network. Specifically, we present a threat taxonomy considering: (i) threats in system-level security, (ii) threats and/or theft of services, and (iii) threats to privacy. Based on the presented threats, we derive a set of security and privacy requirements for SG metering networks. Furthermore, we discuss various schemes that have been proposed to address these threats, considering the pros and cons of each. Finally, we investigate the open research issues to shed new light on future research directions in smart grid metering networks

AUC: Accountable Universal Composability

Accountability is a well-established and widely used security concept that allows for obtaining undeniable cryptographic proof of misbehavior, thereby incentivizing honest behavior. There already exist several general purpose accountability frameworks for formal game-based security analyses. Unfortunately, such game-based frameworks do not support modular security analyses, which is an important tool to handle the complexity of modern protocols. Universal composability (UC) models provide native support for modular analyses, including re-use and composition of security results. So far, accountability has mainly been modeled and analyzed in UC models for the special case of MPC protocols, with a general purpose accountability framework for UC still missing. That is, a framework that among others supports arbitrary protocols, a wide range of accountability properties, handling and mixing of accountable and non-accountable security properties, and modular analysis of accountable protocols. To close this gap, we propose AUC, the first general purpose accountability framework for UC models, which supports all of the above, based on several new concepts. We exemplify AUC in three case studies not covered by existing works. In particular, AUC unifies existing UC accountability approaches within a single framework

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