Smart grid cyber-physical systems: Components, vulnerabilities, mitigations, opportunities, and conceptual framework

Recent developments of the smart grid integrate cyber-physical systems (SG-CPS), information and communication technology, and the Internet of Things (IoT). Specifically, SG energy trading throughout cyber-physical systems (CPS) incorporates IoT-based devices, sensors, and actuators that are operated via both wired and wireless communication technologies. These combinations are essential for monitoring and controlling the operations of supervisory control and data acquisition (SCADA), wide area measurement systems (WAMS), and advanced metering infrastructure (AMI). SG-CPS data communication, processing, and aggregation using both secure and insecure network systems. Thus, the increasing reliance of SG-CPS on communication systems has led to unauthorized access and vulnerabilities, resulting in cyberattacks. Recent literature has reviewed advancements in SG-CPS cybersecurity, focusing on individual components of SG architectures, communication systems, standards, protocols, and security solutions, which include lightweight and authenticated key agreement protocols, machine learning, deep learning, and blockchain. Although notable progress has been made, SG, cyber-physical components, applications, and a cybersecurity roadmap are unavailable. The significance of this study lies in its in-depth understanding of the SG-CPS progression, including its domains, principles, energy trading systems, communication technology, and categorization of general, technical, and security-related standards and protocols. Then, critically discussed cybersecurity perspectives and status, including objectives, requirements, vulnerability zones, advanced solutions, constraints, and research opportunities. Subsequently, the review identified a lack of data aggregation, challenges in data privacy and security, and the need for robust security mechanisms to predict, detect, and mitigate cyber-attacks. Furthermore, based on the findings, it proposes a conceptual framework and process that leverages hash-graph, a lightweight and privacy-preserving quantum-resistant protocol, along with a machine learning approach. Accordingly, it provides a system model, design goals, a three-phase methodology, performance and security assessment metrics, simulation items, environments, and requirements that will guide new and experienced researchers in advancing SG-CPS cybersecurity. • Overview cyber-physical systems for optimize smart grid and advances energy trading systems. • This study categorizes communication technologies, essential standards, and protocols. • Rigorously review on cyber-security perspectives, attack zones, impactedness and recent advancement. • Include challenges and provides significant insights for the futures research directions. • Propose novel conceptual framework support addressed challenges to enhance cyber-security.