Adaptive partial disconnection and graph neural networks against malware propagation

This academic paper explores using graph neural networks (machine learning models that analyze connected data structures) and adaptive partial disconnection (selectively cutting off connections in a network) as methods to stop malware from spreading through systems. The research, published in July 2026, presents these techniques as defensive strategies for protecting networks against malware propagation.