Energy Focused Graph Learning Techniques for Securing Distributed Networks
S.Nithyadhevi, K. Indra Gandhi · 2024
The Internet of Things (IoT) is essential in the modern information technology environment. Following the presence of computers and the internet, IoT has become a significant force driving the global information industry revolution. IoT technologies provide people with clever ideas and more convenient ways to share, communicate, and use critical applications in healthcare, smart homes, urban development, and defense. However, IoT also presents various vulnerabilities and risks commonly associated with its applications. Identifying malicious nodes within IoT networks is a complex and time-intensive endeavor because of the numerous challenging parameters. By concentrating on the energy parameter to develop a targeted and effective approach for detecting malicious nodes, thereby enhancing the security and efficiency of IoT networks. To propose a novel algorithm called the Energy-Driven Node Security Algorithm (ENSA) to address the challenges of identifying malicious nodes based on Graph Neural Networks (GNN). This paper discusses detecting and identifying network security threats and presents corresponding results based on simulation parameters.