Blockchain Technologies for Secure and Transparent Artificial Intelligence Systems
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2024
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| _version_ | 1866901770011148288 |
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| author | Panda, Sibaram Prasad |
| author_facet | Panda, Sibaram Prasad |
| contents | <p>The rapid development and vast deployment of<br>synthetic intelligence (AI) systems have raised great<br>concerns concerning security, transparency, and<br>trustworthiness. This paper explores the integration of<br>blockchain technology as a potential way to deal with these<br>demanding situations in AI systems. We examine the<br>current vulnerabilities in AI architectures and advocate a<br>blockchain-primarily based framework that complements<br>facts integrity, model responsibility, and audit trails during<br>the AI lifecycle. Our research demonstrates that disbursed<br>ledger technologies can provide immutable records of<br>education facts provenance, model development approaches,<br>and inference selections, thereby increasing trust and<br>verification talents. We examine several implementation<br>methods, together with permissioned and permissionless<br>blockchain architectures, smart contract integration for<br>automatic governance, and consensus mechanisms<br>optimized for AI workflows. Performance opinions imply<br>that at the same time as blockchain integration introduces<br>computational overhead, the safety and transparency<br>advantages outweigh those prices in essential programs. We<br>conclude that blockchain-secured AI represents a promising<br>paradigm for growing more strong, accountable, and shrewd<br>trustworthy structures, especially in domains where<br>selection verification and auditability are paramoun</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15397634 |
| institution | Zenodo |
| language | eng |
| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Blockchain Technologies for Secure and Transparent Artificial Intelligence Systems Panda, Sibaram Prasad Blockchain, artificial intelligence, protection, transparency, dispensed ledger generation, smart contracts, version governance, statistics provenance. <p>The rapid development and vast deployment of<br>synthetic intelligence (AI) systems have raised great<br>concerns concerning security, transparency, and<br>trustworthiness. This paper explores the integration of<br>blockchain technology as a potential way to deal with these<br>demanding situations in AI systems. We examine the<br>current vulnerabilities in AI architectures and advocate a<br>blockchain-primarily based framework that complements<br>facts integrity, model responsibility, and audit trails during<br>the AI lifecycle. Our research demonstrates that disbursed<br>ledger technologies can provide immutable records of<br>education facts provenance, model development approaches,<br>and inference selections, thereby increasing trust and<br>verification talents. We examine several implementation<br>methods, together with permissioned and permissionless<br>blockchain architectures, smart contract integration for<br>automatic governance, and consensus mechanisms<br>optimized for AI workflows. Performance opinions imply<br>that at the same time as blockchain integration introduces<br>computational overhead, the safety and transparency<br>advantages outweigh those prices in essential programs. We<br>conclude that blockchain-secured AI represents a promising<br>paradigm for growing more strong, accountable, and shrewd<br>trustworthy structures, especially in domains where<br>selection verification and auditability are paramoun</p> |
| title | Blockchain Technologies for Secure and Transparent Artificial Intelligence Systems |
| topic | Blockchain, artificial intelligence, protection, transparency, dispensed ledger generation, smart contracts, version governance, statistics provenance. |
| url | https://doi.org/10.5281/zenodo.15397634 |