User Isolation Poisoning on Decentralized Federated Learning: An Adversarial Message-Passing Graph Neural Network Approach

Researchers have identified a new attack called user isolation poisoning (UIP) that targets decentralized federated learning (DFL, a system where multiple computers train AI models together without sending raw data to a central server). A malicious participant in DFL can use an adversarial message-passing graph neural network (a type of AI model that shares information between connected nodes) to strategically corrupt their model updates, which tricks the system into ignoring honest participants' contributions and reduces the overall accuracy of the shared model by up to 49.5%.