Industrial Control Systems (ICS) are vital in managing critical infrastructures, including nuclear power plants and electric grids. With the advent of the Industrial Internet of Things (IIoT), these systems have been integrated into broader networks, enhancing efficiency but also becoming targets for cyberattacks. Central to ICS are Programmable Logic Controllers (PLCs), which bridge the physical and cyber worlds and are often exploited by attackers. There\u27s a critical need for tools to analyze cyberattacks on PLCs, uncover vulnerabilities, and improve ICS security. Existing tools are hindered by the proprietary nature of PLC software, limiting scalability and efficiency.
To overcome these challenges, I developed a Virtual PLC Platform (VPP) for forensic analyses of ICS attacks and vulnerability identification. The VPP employs the packet replay technique, using network traffic to create a PLC template. This template guides the virtual PLC in network communication, mimicking real PLCs. A Protocol Reverse Engineering Engine (PREE) module assists in reverse-engineering ICS protocols and discovering vulnerabilities. The VPP is automated, supporting PLCs from various vendors, and eliminates manual reverse engineering. This dissertation highlights the architecture and applications of the VPP in forensic analysis, reverse engineering, vulnerability discovery, and threat intelligence gathering, all crucial to bolstering the security and integrity of critical infrastructure
