A Modeling Attack-Resistant PUF-Enabled Robust Authentication and Key Agreement Scheme for Industrial Wireless Sensor Networks

Industrial wireless sensor networks (IWSNs) are emerging as a new network paradigm in Internet of Things (IoT) for smart manufacturing, monitoring, and automation systems. IWSNs seamlessly integrate with IoT platforms and cloud services to support advanced services such as remote monitoring, AI-powered analytics, and advanced automated control. However, these systems can be vulnerable to potential security attacks because an adversary can attempt to delete, modify, intercept, and block the transmitted messages over an insecure channel. Besides cybersecurity attacks, IoT devices may be vulnerable to physical security attacks because they are deployed in unattended environments. To resolve these security threats and weaknesses, robust and lightweight authentication and key agreement (AKA) schemes are essential. Many researchers have recently presented a PUF-based secure and lightweight AKA scheme for IWSN-based IoT. Unfortunately, we demonstrated that the previous scheme is susceptible to potential security threats and does not guarantee the necessary security functionalities. Moreover, the existing PUF-based AKA schemes may be vulnerable to machine learning (ML)-based modeling attacks. Thus, we propose a ML-based modeling attack-resistant PUF-enabled robust AKA scheme for IWSN-enabled IoT to improve the security flaws of the previous scheme, called PUF-IWSN. We evaluate the security of PUF-IWSN by performing formal security analysis such as AVISPA simulation and ROR oracle model. We demonstrate the analysis of performance comparison between PUF-IWSN and its related schemes. We present the implementation to evaluate the security of existing PUFs and the hybrid PUF against ML-based modeling attacks. Consequently, PUF-IWSN ensures superior efficiency and security than the previous schemes and can be suitable for practical IWSN-enabled IoT systems.