A Hybrid Iris Recognition System Model Based on Presentation Attack Detection and Traffic Monitoring Module on AIoT System

The integration of AI technology with IoT devices, as in the case of Artificial Intelligence of Things (AIoT), has enabled more efficient and intelligent processing and analysis of data than traditional IoT systems. However, the use of biometric information by AIoT devices can pose new security risks, such as presentation attacks and privacy breaches, particularly for immutable features such as iris information, which can lead to long-term security vulnerabilities when compromised. Most existing iris recognition system security models are currently designed to address only direct presentation attack algorithms. Therefore, such models cannot address other security threats. To address these challenges, this study proposes a hybrid iris recognition system security protection model that employs presentation attack detection, flow monitoring, and black list restrictions to enhance the overall security of AIoT devices and improve the efficiency of protection. Specifically, the model aims to prevent presentation attacks and flow attacks against the iris recognition system, which may compromise the security of biometric information. The proposed method is expected to increase AIoT devices security against potential threats to sensitive information.