Progressive Binding Commitments: Adaptive Consensus-Optimized Cryptographic Frameworks for Secure Blockchain-Based Data Sharing
Keywords:
Blockchain, Secure Data Sharing, Adaptive Consensus, Reinforcement Learning, Zero-Knowledge Proofs, Hyperledger FabricAbstract
Abstract–We propose a Progressive Binding Commitment Framework (PBCF) that redefines data access and revocation management in decentralized cloud environments by decomposing the commitment lifecycle into three cryptographic states: preliminary, intermediate, and verified. Traditional blockchain-based data sharing systems treat every access grant or revocation as a monolithic transaction requiring immediate finality, which introduces significant latency and scalability bottlenecks. The proposed framework addresses this limitation through a staged Merkle-Patricia Trie hashing mechanism embedded within the smart contract layer, where each state corresponds to a progressively stronger binding between the data access grant and the immutable ledger. An adaptive consensus routing module, driven by a deep Q-network reinforcement learning agent, dynamically selects which commitments to finalize based on real-time network conditions such as block production interval, pending transaction queue length, and validator response time. This agent outputs a policy that prioritizes preliminary commitments for routine data exchanges while deferring intermediate-to-verified transitions for sensitive operations, thereby optimizing throughput and reducing delay. Furthermore, the framework integrates asynchronous zero-knowledge proof generation for permission withdrawal queries, enabling revocation notifications to propagate within milliseconds via a dedicated proof-of-stake sidechain without blocking the main chain’s transaction processing. A policy preprocessor computes a sensitivity score for each data object using a gradient-boosted decision tree trained on historical access patterns, which determines the initial commitment state and dynamically adjusts thresholds based on network congestion. The concrete implementation on Hyperledger Fabric v2.5 demonstrates that the system maintains an average data sharing latency under 200 milliseconds for routine operations while cryptographically enforcing sensitive revocations within five seconds, even under 90% network load. The primary contribution lies in the novel integration of progressive cryptographic commitments with adaptive consensus optimization, which fundamentally improves the scalability and responsiveness of decentralized data sharing frameworks.
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