Revisiting Label Inference Attacks in Vertical Federated Learning: Why They Are Vulnerable and How to Defend
Revisiting Label Inference Attacks in Vertical Federated Learning: Why They Are Vulnerable and How to Defend explores This research reveals vulnerabilities in vertical federated learning label inference attacks and proposes a zero-overhead defense by adjusting model layers to improve privacy.. Commercial viability score: 4/10 in Federated Learning.
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