A Hybrid Security Methodology for Real-Time Constraint Cyber-physical Systems

Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA) systems play an important role in automating and optimizing industrial processes in sectors such as manufacturing, energy, and transportation. They enhance productivity and reliability by providing real-time monitoring and control capabilities. The integration of advancements in the Internet of Things (IoT), Artificial Intelligence (AI), and predictive modeling has further enhanced the effectiveness of ICS, enabling real-time data analytics, adaptive control, and predictive maintenance. However, increased connectivity introduces significant cybersecurity risks. This paper examines vulnerabilities in ICS communication protocols, specifically Modbus and Distributed Network Protocol 3 (DNP3). It highlights the lack of built-in security in Modbus and the enhanced security features of DNP3. The paper explores vulnerabilities such as software flaws, configuration errors, and communication weaknesses, which can lead to unauthorized access and data breaches. Additionally, it discusses the importance of network security and proposes methodologies to secure Cyber-Physical Systems (CPS), including Lightweight Encryption Algorithms (LEA), Robust Encryption Algorithms (REA), Multi-Factor Authentication (MFA), and Machine Learning (ML)-based Intrusion Detection Systems (IDS). By analyzing existing research and presenting practical solutions, this paper aims to enhance the security and reliability of ICS and CPS, ensuring the protection of critical infrastructure against evolving cyber threats.