PureChain-Enabled Framework for Trustworthy and Incentivized Smart Contract Vulnerability Detection

Smart contract vulnerabilities pose a critical threat to blockchain-enabled Internet of Things (IoT) systems, as they can lead to substantial financial losses and undermine trust in decentralized services. While existing studies demonstrate strong vulnerability detection performance, they often overlook trust alignment, incentive compatibility, and verifiable validation under adversarial conditions. This study presents a trustworthy and incentivized framework for smart contract vulnerability governance that integrates decentralized reporting, a Proof of Authority and Association (PoA2) reputation mechanism, proof-of-concept (PoC)-assisted validation and hybrid on-chain/off-chain orchestration. The main contribution of this study lies in the PoA2-based trust and incentive model, which quantifies the reliability of the participants through the authority, association and behavioral trust scores. This mechanism effectively discourages Sybil attacks, collusion, and reward manipulation. Within the framework, vulnerability detection is carried out by an optimized DeepFusion model augmented with expertrule integration, designed as a modular detection engine rather than the primary contribution. Experimental results on bench-mark datasets demonstrate strong performance, achieving F1-scores of up to 97.14% across multiple vulnerability categories, with inference latency ranging from 0.0011 to 0.0116s. By offloading computation-intensive tasks while preserving on-chain auditability, PureChain reduces on-chain overhead and improves scalability. In general, the results indicate that the proposed study provide a practical and trustworthy foundation for the reporting, validation, and incentive-driven security governance of decentralized vulnerabilities in blockchain-based IoT environments.