The rapid expansion of Internet of things (IoT) devices has transformed numerous sectors by enabling extensive connectivity and automation. However, this surge in IoT adoption has also heightened cybersecurity risks, as many IoT devices are resource-constrained and lack robust security measures, making them attractive targets for cyberattacks. Traditional cybersecurity solutions often fail to address the dynamic and constrained IoT environment. Artificial Immune Systems (AIS) have emerged as a novel approach to fortify cybersecurity in IoT networks. Inspired by the human immune system, AIS provides adaptive, self-organizing, and scalable defenses capable of detecting and mitigating diverse cyber threats in real-time. This paper investigates the integration of six AIS into IoT networks, illustrating how these biologically inspired algorithms can effectively identify anomalies, learn from new threats, and maintain system integrity with minimal human oversight. Through a comprehensive review of existing research and practical applications, we demonstrate the effectiveness of AIS in delivering robust, autonomous, and resilient cybersecurity solutions designed for the complex and ever-evolving IoT environment. The findings confirm AIS’s high efficiency in IoT security, with NSA and AIN models demonstrating superior performance and scalability for extensive IoT deployments. Using AIS’s dynamic and adaptive characteristics, IoT environment novices can achieve enhanced protection against complex cyber threats, thus promoting modern interconnected systems’ safe and efficient functioning.