Image-based security techniques for water critical infrastructure surveillance

Abstract

Security-related image analysis of critical infrastructures involves using advanced technologies to analyze visual data to identify potential threats, vulnerabilities, or abnormal activities. This type of analysis can be crucial for safeguarding critical infrastructure such as water management systems, power plants, transportation systems, communication networks, and more. In this paper, we propose two-factor-based authentication and pose-based monitoring tasks for water critical infrastructures. In the first phase, we detect and recognize the faces of authorized persons and check their liveness for anti-spoofing by eye-clicking checking and multimodal ensemble methods. In the second phase, we create our dataset, WCI-Pose, and we use four pose-based approaches – OpenPose, AlphaPose, Kapao, and YOLOv8 – for human action recognition. Experimental results show that OpenPose algorithm provides more favorable results compared to the other algorithms with an accuracy of 92.4%. SVM with multimodal data has the best performance score with an accuracy of 92% for face anti-spoofing.