Trustworthy AI for secure and robust machine learning through blockchain enabled data integrity
Abstract Modern machine learning (ML) systems, especially those trained or updated across multiple parties, are vulnerable to data poisoning, model theft, and adversarial manipulation when provenance and update integrity are not verifiable. Blockchain technology, renowned for its immutability, trans...
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| Автори: | , , , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Springer
2026-05-01
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| Серія: | Discover Artificial Intelligence |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1007/s44163-026-01443-5 |
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