Machine Learning-Based Threat Detection for Personal IoT Devices

Improving the security of the Internet of Things (IoT) is essential due to the growing quantity of IoT devices, which provide new cybersecurity concerns. This paper explores the topic of enhancing Internet of Things security by applying artificial intelligence (AI). We hope to improve the identification of intrusions, reduce insider risks, and detect IoT-botnet assaults by evaluating different AI approaches. Our study aims to provide useful information to strengthen the IoT ecosystem’s resilience in the face of a variety of devices, privacy issues, and changing cyberthreats. This initiative aims to enhance cybersecurity solutions customized for the Internet of Things by bridging the theory–practice divide. The investigation provides practical suggestions for addressing new cyberthreats and emphasizes how crucial it is to protect connected gadgets that are essential to modern life.