Universal and Scalable Security Assessment Standards for Resource-Constrained IoT Environments Bridging the Flexibility-Consistency Paradox

The increasing number of Internet of Things (IoT) devices, especially in resource-limited settings such as low-power sensors, wearable devices, and industrial equipment, has posed serious challenges to ensuring strong security. Such issues are further compounded by weaknesses in processing capabilities, memory, and battery life, which make the deployment of conventional security frameworks difficult. The current paper presents a new security evaluation model, FSRC-IoTE (Flexible Security Resource-Constrained IoT Environments), that will solve these problems by creating universal, scalable, and adaptable security standards specifically applied to IoT-based devices in resource-constrained environments. The framework has sought to resolve the flexibility-consistency paradox and allows flexibility in security solutions that are consistent across all IoT deployment conditions. The main characteristics of the suggested framework are real-time security assessment, simplistic security assessment tools, and AI-based threat detection and mitigation systems. The adaptive mechanisms also discussed in the paper dynamically adjust the criteria of security assessment, depending upon the capabilities of the device and the context of the environment. In comparison with the current methods, this study demonstrates that FSRC-IoTE is far more improved in the context of scalability, flexibility, and real-time security surveillance. The paper ends with recommendations for standardized security practices that can be implemented across IoT devices and which will provide resiliency, as well as trustworthiness, and provide recommendations on how future IoT systems may be developed. The results of this study help in sealing the most critical gaps in the existing criteria pertaining to IoT security to offer a long-term, sustainable answer to the issue of securing resource-constrained IoT settings. The proposed research directions in the future involve additional incorporation of the framework with the new IoT technology and the introduction of the framework into more severely constrained settings.