SOURCE-LINKED INTELLIGENCE

Trust-But-Verify: Poisoning-Resilient Locally Private Graph Learning Protocols

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Built upon local differential privacy (LDP), locally private graph learning protocols have emerged as an important paradigm for decentralized graph learning, balancing privacy protection and learning utility. Under such protocols, each user locally perturbs their node features and adjacency information before transmission, ensuring formal privacy guarantees without original data leaving the device. However, the inherently open participation nature renders these protocols critically vulnerable to data poisoning attacks, where adversaries inject carefully crafted malicious nodes to corrupt neigh

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