#threat-modeling News & Analysis

3 articles tagged with #threat-modeling. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBearisharXiv – CS AI · Apr 107/10

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Physical Adversarial Attacks on AI Surveillance Systems:Detection, Tracking, and Visible--Infrared Evasion

This research paper examines physical adversarial attacks on AI surveillance systems through a surveillance-oriented lens, emphasizing that robustness cannot be assessed from isolated image benchmarks alone. The study highlights critical gaps in current evaluation practices, including temporal persistence across frames, multi-modal sensing (visible and infrared), realistic attack carriers, and system-level objectives that must be tested under actual deployment constraints.

AIBearisharXiv – CS AI · Mar 117/10

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Security Considerations for Multi-agent Systems

A comprehensive study reveals that multi-agent AI systems (MAS) face distinct security vulnerabilities that existing frameworks inadequately address. The research evaluated 16 AI security frameworks against 193 identified threats across 9 categories, finding that no framework achieves majority coverage in any single category, with non-determinism and data leakage being the most under-addressed areas.

AINeutralarXiv – CS AI · Mar 57/10

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Goal-Driven Risk Assessment for LLM-Powered Systems: A Healthcare Case Study

Researchers propose a new goal-driven risk assessment framework for LLM-powered systems, specifically targeting healthcare applications. The approach uses attack trees to identify detailed threat vectors combining adversarial AI attacks with conventional cyber threats, addressing security gaps in LLM system design.