Robotic Cloud Automation-Enabled Attack Detection and Command Verification Using Attention-Based RNNs, ConvLSTM, and Bayesian Networks

Background Information: The emergence of robotic cloud automation has brought about freshcybersecurity hurdles, particularly in protecting communication and control systems fromcyber threats. It is crucial to guarantee strong intrusion detection and verify commandseffectively.Objectives: Create an AI framework by combining deep learning and probabilistic models toimprove intrusion detection and command verification in cloud-based robotic systems.Methods: The system combines Attention-Based RNN, ConvLSTM, and Bayesian Networksto identify abnormalities and authenticate instructions, utilizing temporal and spatial data forinstant threat identification.