A digital forensic framework for investigating Robot Operating System (ROS) environments

Robotic systems in delicate fields like manufacturing, healthcare, and defence have created difficult forensic and security issues. The popular robotics software known as Robot Operating System (ROS) is modular, decentralised, and devoid of built-in security features. Because traditional digital forensic techniques are designed for centralised computing systems, these features make their application more difficult. A new forensic framework designed specifically for ROS-based systems, the Robot Operating System Forensic Framework (ROSFF), is presented here. In contrast to conventional forensic models, ROSFF resolves the odd ROS structure by combining procedures and tools that facilitate decentralised logging, distributed evidence collection, and real-time monitoring. Because it integrates the three areas of investigation: technical, organisational, and legal. The forensic process becomes scalable, methodical, and also morally and legally sound. With the help of anomaly detection and event tracing, ROSFF is constructed using four fundamental steps: data acquisition, analysis, examination, and reporting. When compared to other forensic models, ROSFF is more adaptable, provides comprehensive evidence, and can be used with robotic systems. The results demonstrate that ROSFF is a useful tool for conducting efficient forensic investigations and safeguarding ROS environments. This work lays the groundwork for upcoming digital forensic operations in autonomous systems and fills a major knowledge gap in robotic cybersecurity.