Real-Time Threat Detection and Countermeasures in IoT Environments

As the Internet of Things (IoT) expands rapidly into new industries such as healthcare, transportation, and smart cities, the security of these interconnected devices becomes increasingly important. The research work includes a thorough investigation into the design and implementation of real-time threat detection techniques and subsequent responses for IoT environments. Our suggested solution identifies potential security breaches and abnormalities at an unparalleled rate by combining advanced machine learning algorithms and behavior-based analysis. The system rapidly launches countermeasures upon detection, ensuring minimal data loss and system disruption. Using a simulated IoT network environment, the experimental findings showed a detection accuracy of 98.7
^%
and a false positive rate of less than 2 %. The incorporation of these real-time threat detection algorithms not only strengthens IoT systems but also prepares the way for the creation of more resilient smart infrastructures. This study emphasizes the necessity of proactive security measures and offers a roadmap for safeguarding the next generation of IoT devices.