Malicious Node

Malicious nodes, nodes exhibiting anomalous or adversarial behavior within a network, pose significant challenges across diverse domains, from financial fraud detection to critical infrastructure security. Current research focuses on detecting these nodes using graph neural networks (GNNs), often incorporating techniques like adaptive sampling, attention mechanisms, and reinforcement learning to improve accuracy and robustness, even in the presence of noisy data or camouflage. These advancements are crucial for enhancing the security and reliability of various networked systems, impacting fields ranging from cybersecurity and finance to smart grids and human-robot interaction.