Secure and Lightweight Authentication Protocol Using PUF for the IoT-based Wireless Sensor Network

The wireless sensor network (WSN) has been gaining popularity for automation and performance improvement in different IoT-based applications. The resource-constrained nature and operating environment of IoT make the devices highly vulnerable to different attacks. On the other hand, the Physically Unclonable Function (PUF) helps to implement secure and lightweight authentication protocols for IoT. In this context, few computation-intensive authentication protocols are found in the literature that have addressed secure IoT communication in WSN. Besides, these protocols depend on the local storage of PUF-CRP, which is susceptible to security attacks. This work proposes a lightweight and secure authentication protocol for the IoT devices in WSN. A PUF and its machine learning (ML)–based soft model is integrated to ensure secure authentication and lightweight computation in WSN. PUF prevents physical attacks while carrying very less hardware fingerprints, and the ML-based PUF provides the desired resiliency against PUF identity-based attacks by eliminating the requirement of CRP-based storage. The proposed mechanism delivers two-way authentication while nullifying the attacks on IoT. The proposed protocol is implemented on Xilinx Artix-7 FPGA and Raspberry Pi for testability and performance evaluation. Experiment results and analysis signify its low-cost computations and lightweight features desired for IoT.