Abstract of doctoral thesis - Stylianos Katsoulis

"Internet of Things and Cloud Computing with emphasis on security in intelligent environments"


The subject of the proposed doctoral dissertation is the study of intelligent systems for measuring and monitoring physical quantities with emphasis on security and privacy. The use of improved routing protocols creates a fast, efficient system with low power consumption, network resources and processing power. The rapid development of semiconductor technology has created low-cost devices that allow the integration of wireless interfaces into microprocessors and sensors (ESP8266 with ESP32 successor). This interconnection is via WiFi and in future with the development of the mobile network it will furthermore allow the interconnection via 5G. A major issue to be investigated is the pre-processing of data to save network resources and energy, as the reception of data from a large system is difficult and the large-volume traffic makes processing more difficult. The large volume of data involved makes it necessary to use NoSQL databases in cloud infrastructures. Decision making requires computational intelligence (CI) with Machine Learning (ML) and Deep Learning (DL) techniques. At this point, algorithms that are efficient in terms of speed and reliability for decision-making should be studied. Another issue that concerns investigation is the integrity, security and privacy of data. As the growing tendency to use smart devices such as lighting, electronic switches, security systems, entertainment, etc. creates large systems and allows unwanted invasion of potential safety gaps. Therefore, all of this amalgam of IoT systems is difficult to control. Sensors that control the status of certain conditions in applications such as street lighting, lack resources in network security. The use of multiple data networks that serves as bridges for their interconnection in the final network poses risks and data encryption is required. A network layout with security protocols using cryptographic algorithms will be studied. Another area to be investigated is Network Traffic Monitoring, which will monitor the network traffic and it will be able to detect possible abnormal behavior. It will be able to detect the source of the problem, inform the administrators and isolate it if required.