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...

詳細記述

書誌詳細

主要な著者:	Seid Mehammed Abdu, Girma Bewuketu, Demeke Getaneh, Md Nasre Alam, Armilyn Cosico Fernandez, Anna Beth Amante Basco, Zafrul Hasan, Mohammad Serajuddin
フォーマット:	Artigo
言語:	Inglês
出版事項:	Springer 2026-05-01
シリーズ:	Discover Artificial Intelligence
主題:	Machine learning Blockchain Data integrity Federated learning Trustworthy AI Cybersecurity
オンライン･アクセス:	https://doi.org/10.1007/s44163-026-01443-5
タグ:	タグ追加 タグなし, このレコードへの初めてのタグを付けませんか!