AITA: Accurate Network Topology Recognition via Active Interception and Topology Analysis
Rui Sun · 2024
Recent advances in wireless communication technologies have ushered in a significant opportunity to revolutionize the new network communication and combat strategies. The high efficiency of modern communication war requires that the key nodes and topology of wireless communication organization can be easily mastered with low computing cost. In complex and diverse communication situations, accurate identification of network topology becomes a key problem to improve communication efficiency and performance optimization. Traditional topology identification algorithms often rely on a single technology or data source, there are various communication environments and dynamic topology, so a more comprehensive and accurate method is needed. In this paper, we proposed a novel method called AITA for accurate topology identification of complex communication networks by a structured fusion of active listening and topology analysis. Specially, it involves sending out the interfering crafted packets to devices within the network and observing their responses to infer the topology. The topology analysis strategies, including graph theory and structured modeling, are automatically triggered to enhance the precision of topology identification in the presence of a significant error in the estimated location of active interception. Experimental results show that the proposed method performs well in accuracy, power consumption and recognition performance, and is superior to the traditional single detection and recognition methods. It provides a feasible and efficient solution to the topology identification problem in modern communication warfare, which lays the foundation for the future intelligent and adaptive communication system.