Lightweight Multi-Agent Edge Framework for Cybersecurity and Resource Optimization in Mobile Sensor Networks

Due to the growth of smart cities, many real-time systems have been developed to support smart cities using Internet of Things (IoT) and emerging technologies. They are formulated to collect the data for environment monitoring and automate the communication process. In recent decades, researchers have made many efforts to propose autonomous systems for manipulating network data and providing on-time responses in critical operations. However, the widespread use of IoT devices in resource-constrained applications and mobile sensor networks introduces significant research challenges for cybersecurity. These systems are vulnerable to a variety of cyberattacks, including unauthorized access, denial-of-service attacks, and data leakage, which compromise the network’s security. Additionally, uneven load balancing between mobile IoT devices, which frequently experience link interferences, compromises the trustworthiness of the system. This paper introduces a Multi-Agent secured framework using lightweight edge computing to enhance cybersecurity for sensor networks, aiming to leverage artificial intelligence for adaptive routing and multi-metric trust evaluation to achieve data privacy and mitigate potential threats. Moreover, it enhances the efficiency of distributed sensors for energy consumption through intelligent data analytics techniques, resulting in highly consistent and low-latency network communication. Using simulations, the proposed framework reveals its significant performance compared to state-of-the-art approaches for energy consumption by 43%, latency by 46%, network throughput by 51%, packet loss rate by 40%, and denial of service attacks by 42%.