Federated learning blockchain

federated learning blockchain

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In: Artificial intelligence and statistics, H et al Private federated learning on vertically partitioned data.

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It also works well against security attacks such as Denial of Service DoS , reverse model poisoning, and free-riding attacks. Attacks to federated learning architecture. Therefore, consensus and incentive schemes are wisely implemented, which successfully motivate the communication of data in FL. System heterogeneity 3. To prevent tampering, smart contracts are copied to each node in the blockchain.