Zero-Knowledge-Proof-Based Anomaly Detection: Conclusion & Referencesby@quantification

Zero-Knowledge-Proof-Based Anomaly Detection: Conclusion & References

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This conclusion introduces a pioneering anomaly detection technique designed for practical application in real-world Federated Learning systems. The method employs an early cross-round check and Zero-Knowledge Proofs to efficiently detect and remove anomaly client models during attacks, preserving the integrity of benign submissions. The approach is well-suited for real-world FL, with future plans extending its capabilities to asynchronous FL and vertical FL scenarios.

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by Quantification Theory Research Publication @quantification.The publication about the quantity of something. The theory about why that quantity is what is. And research!
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