Forensic Investigation in Robots
Abstract
Integrating robots into industrial automation has led to a revolutionary transformation in executing complex tasks, harnessing precision and efficiency. The Robot Operating System (ROS) has played a significant role in driving this advancement. ROS Bag files in robots are crucial for preserving data, as they provide a format for recording and playing back ROS message data. These files serve as a comprehensive log of a robot's sensory inputs and operational activities, enabling detailed analysis and reconstruction of the robot's interactions and performance over time. However, there have been instances where security considerations were overlooked, giving rise to concerns about unauthorized access, data theft, and malicious actions. This research investigates the forensic potential of data generated by robots, with a particular focus on ROS Bag data. By analyzing ROS Bag data, we aim to uncover how such information can be used in forensic investigations to reconstruct events, diagnose system failures, and verify compliance with operational protocols. The components of the ROS ecosystem were examined, identifying the challenges in parsing ROS Bag files and underscoring the need for specialized tools. This analysis highlights the security risks associated with plain text communication within legacy ROS systems, emphasizing the importance of encryption. While providing valuable insights, this research calls for further exploration, tool development, and enhanced security practices in robotics and digital forensics, aiming to lay the foundation for effective crime resolution involving robots.
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