부산대학교 도서관

The Internet of Things (IoT) facilitates connectivity between smart environments such as homes, cities, health systems and the web. The proliferation of IoT devices, with their unique characteristics and security challenges, requires robust security solutions. This study explores the integration of Software-Defined Networking (SDN) with the Internet of Things (IoT) to enhance network management and security. Through a proposed framework incorporating a customized Sensor OpenFlow Switch (SOFS) and security offers based on ML this experiment evaluates effectiveness of different algorithms in detecting attacks across varying numbers of loT nodes. Results show comparable performance among classifiers and highlight the efficiency of decision tree-based algorithms in SD-IoT networks.