aspg-2-2731-1791417387 20261007235627 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Cybersecurity and Information Management JCIM 2769-7851 2690-6775 2024 13 2 Abedallah Zaid Abualkishik American University in the Emirates, Dubai, UAE Nodira Zikrillaeva Tashkent State University of Economics, Uzbekistan Gulyamova Gulnora International Islamic Academy of Uzbekistan, Uzbekistan This research shows a complete security design for Internet of Things (IoT) devices. It improves security by using five methods that work together. At the beginning of the process, a machine learning-based method for ranking changes is used. Then, architectures are put in place for scalable patch distribution, anomaly detection, dynamic risk assessment, and integrating threat data. Using five connected algorithms, the purpose of this research is to create a complete security framework for Internet of Things devices. Dynamic risk assessment, scalable patch delivery, integration with threat intelligence, and anomaly detection for zero-day vulnerabilities are among its characteristics. It also identifies zero-day vulnerabilities. Furthermore, it prioritises repairs using machine learning data. Every solution seeks to address a specific component of IoT security, such as dynamic risk assessments, effective patch distribution, and patch prioritisation based on vulnerability data. It is critical to maintain the Internet of Things ecosystem's safety, flexibility, and efficiency. An integrated approach provides a strong defence against cyberattacks, which is crucial for ecosystem preservation.With this system, you can get better accuracy, flexibility, and resource use than with other methods. To help explain how the methods work, charts and flowcharts are used. The ablation study indicates that each method is important because it shows how they all help keep IoT devices safe. The suggested design considers how cyber risks are always changing to protect connected devices in a lot of different places from hackers. 2024 30 49 2731 https://creativecommons.org/licenses/by/4.0/ 10.54216/JCIM.130203 https://www.americaspg.com/journal/2/article/2731 https://www.americaspg.com/storage/61714360640.pdf