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NIST Adversarial Machine Learning Taxonomies: Decoded, IPLR-IG-016
2025
ISBN
978-81-986924-6-7
Author(s)
Gargi Mundotia, Sneha Binu, Yashita Parashar
Editor(s)
Not Applicable
IndoPacific.App Identifier (ID)
IPLR-IG-016
Tags
Accountability, adversarial AI, adversarial machine learning, anomaly detection, Artificial Intelligence, attack taxonomy, BFSI, citizen data governance, cyber attacks, cybersecurity, data analysis, data poisoning, deepfake fraud, defense strategies, Digital Public Infrastructure, DPI, encryption NIST standards details ethical AI guidelines, evasion attacks, fraud detection, infrastructure attacks, large language models, LLMs, Machine Learning, mitigation strategies, NIST, NIST AI 100-2 E2025, pattern recognition, poisoning attacks, predictive AI systems, regulatory compliance, sector-specific threats, telecommunication, threat response, Transparency, zero-trust frameworks
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