PrivChain-AI leveraging blockchain and federated learning for private financial reporting and access control
Saad Alaklabi

TL;DR
PrivChain-AI is a new system that uses blockchain and machine learning to securely share financial data while protecting privacy and complying with regulations.
Contribution
The novel integration of blockchain, federated learning, differential privacy, and smart contracts for secure financial reporting.
Findings
PrivChain-AI achieves 94.7% accuracy in fraud detection with ϵ = 1.0 differential privacy.
The system is 40% faster in communication overhead and ensures immutable audit trails for compliance.
Privacy preservation improves by 78% and access control granularity by 62% compared to existing methods.
Abstract
Financial institutions are currently faced with suffering never experienced before as they strive to guarantee the privacy of data and address the demands of regulation to report and cooperate in machine learning. This paper proposes PrivChain-AI, a novel blockchain-based federated learning system designed to facilitate secure and privacy-preserving financial reporting and access control. The proposed framework will integrate three key components: differential privacy, homomorphic encryption, and smart contract-based governance, enabling cooperative model training across financial institutions while preventing the leakage of sensitive information. PrivChain-AI is a hierarchical design that incorporates permissioned consensus protocols and utilises zero-knowledge proof verification to authenticate transactions. It has been demonstrated that the performance is higher than that of the…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Privacy-Preserving Technologies in Data · Cryptography and Data Security
