The escalating development of artificial intelligence and machine learning in Industry 4.0 and cyber-physical systems has heightened security challenges for humans. In addressing this, Physical Unclonable Functions (PUFs) have emerged as a promising, lightweight solution to enhance the security of Internet of Things (IoT) devices. The imperative need for secure and low-power cryptographic devices has become evident in the IoT domain and its evolving technologies. Although IoT has enabled battery-operated devices to transmit sensitive data, it has also introduced challenges, including high power consumption and security vulnerabilities. This paper presents an exploration of the utilization of adiabatic logic with carbon nanotube field-effect transistors (CNTFETs) for the design of lightweight IoT devices aimed at addressing these challenges. The proposed computing platform and architecture circuit, employing Static Random-Access Memory (SRAM), demonstrate the potential to enhance security and energy efficiency for IoT applications. Our research showcases highly resilient CNTFET and adiabatic logic-based SRAM-PUFs, exhibiting an ultra-low start-up power of 1.8 nw. The PUF metrics, including uniformity, reliability, and uniqueness, are 46.10%, 88.47%, and 48.84%, respectively, across a 150% process variation. In this paper, we conduct circuit simulations using 32nm CNTFET technology in HSpice to scrutinize the impact of threshold voltage fluctuations. Further post-processing procedures are executed using MATLAB software.