aceMultimodal Graph Neural Networks and Evolutionary Knowledge Fusion for Secure and Explainable Governance in Intelligent IoT Interactive Media Systems
This research proposes a secure, explainable, and context-aware governance framework for blockchain-based digital media contracts in multimodal artificial intelligence-enabled AIoT interactive systems. As digital licensing, NFT copyright management, royalty distribution, and cross-chain content circulation become increasingly embedded in smart media ecosystems, existing contract auditing approaches remain limited by unimodal analysis, weak explainability, black-box decision processes, and insufficient cross-plat…
The proposed AI framework enables more robust detection of copyright misuse, unauthorized licensing and cross-chain transaction risks in blockchain media contracts.
Evidence
- Peer-reviewedBig Data2026-09-02
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Truvace Impact Record TRV-2026-0965, v2: “Multimodal Graph Neural Networks and Evolutionary Knowledge Fusion for Secure and Explainable Governance in Intelligent IoT Interactive Media Systems.” Truvace, 2026-10-26. /record/TRV-2026-0965 (accessed at citation time). sha256 bde9671cc3cdf082…
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