2 papers
cs.AI2026
Improving Methodologies for Agentic Evaluations Across Domains: Leakage of Sensitive Information, Fraud and Cybersecurity Threats
Ee Wei Seah, Yongsen Zheng, Naga Nikshith +67
The rapid rise of autonomous AI systems and advancements in agent capabilities are introducing new risks due to reduced oversight of real-world interactions. Yet agent testing rema…
cs.LG2023
The race to robustness: exploiting fragile models for urban camouflage and the imperative for machine learning security
Harriet Farlow, Matthew Garratt, Gavin Mount +1
Adversarial Machine Learning (AML) represents the ability to disrupt Machine Learning (ML) algorithms through a range of methods that broadly exploit the architecture of deep learn…