PoL-BFL: Towards Trustworthy Federated Learning with Zero-Knowledge Proofs and Verifiable Incentives
PoL-BFL is proposed, a framework that bridges a critical verification gap through a novel "verify-then-slash" paradigm to make verification economically decisive rather than exhaustive, and proves that honest participation is strictly more profitable than cheating for rational clients whenever the detection probability...