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New Research Decodes NIST Adversarial ML Standards for Indian Enterprises

Communications Team
3 days ago
1 min read

Indic Pacific Legal Research LLP today released "NIST Adversarial Machine Learning Taxonomies: Decoded" (IPLR-IG-016, First Edition 2025), a comprehensive analysis of emerging AI cybersecurity threats and mitigation strategies.

Download: https://indopacific.app/product/nist-adversarial-machine-learning-taxonomies-decoded-iplr-ig-016/

📈 Research Highlights:The publication, authored by cybersecurity researchers Gargi Mundotia, Yashita Parashar, and Sneha Binu, translates complex NIST AI 100-2 E2025 standards into actionable intelligence for Indian organizations across critical sectors.

🏦 Sector-Specific Focus: The research addresses unique vulnerabilities in Banking & Financial Services (regulatory compliance in AI fraud detection), Telecommunications (deepfake attacks), and Digital Public Infrastructure (citizen data governance concerns).

⚡ Dual-Use Technology Challenge: As AI enhances cyber defense capabilities, the same technology enables sophisticated attacks including adversarial AI and data poisoning - creating an evolving threat landscape requiring specialized countermeasures.

Download: https://indopacific.app/product/nist-adversarial-machine-learning-taxonomies-decoded-iplr-ig-016/

"This research fills a critical gap by making international cybersecurity standards practically applicable for Indian enterprises around adversarial machine learning," said Abhivardhan, our Founder.