Creating a security conscious IoT ecosystem with innovative monitoring and classification solutions

Abstract

The Internet of Things (IoT) is one of the most dynamically developing areas of technology today. In IoT systems, everyday devices—such as smart home appliances, industrial sensors, and medical devices—are connected to a network and collect and exchange data with each other. However, the spread of these technologies also carries a number of security risks. The aim of this doctoral thesis is to provide a comprehensive overview of the security challenges of IoT systems and to show how effective protection and monitoring solutions can be developed. In my research, I examine how different security classes can be created and how they can be adapted to IoT devices with limited resources. In addition, I aim to develop a test sample measurement that helps classify devices into the security classes I have defined. The research also includes the design of a spectrum monitoring environment capable of continuously monitoring and evaluating the communication processes of IoT networks and identifying any anomalies. The developed system enables the automatic detection and classification of disruptive, faulty, or suspicious devices, thereby contributing to the increased reliability and security of IoT infrastructures. The results of the dissertation are expected to contribute to the development of a decision support framework that will enable developers and operators to improve the security level of IoT systems in a measurable and targeted manner. The results of the dissertation contribute to the development of a decision support framework that helps developers and operators improve the security level of IoT systems in a measurable and targeted manner.