Copertina

A Practical Framework for Evaluating Medical AI Security: Reproducible Assessment of Jailbreaking and Privacy Vulnerabilities Across Clinical Specialties

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Jinghao, Zhang, Ping, Yagemann, Carter
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Cryptography and Security Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

C2RUST-BENCH: A Minimized, Representative Dataset for C-to-Rust Transpilation Evaluation
di: Sirlanci, Melih, et al.
Pubblicazione: (2025)

Breaking the Code: Security Assessment of AI Code Agents Through Systematic Jailbreaking Attacks
di: Saha, Shoumik, et al.
Pubblicazione: (2025)

Data Poisoning Vulnerabilities Across Healthcare AI Architectures: A Security Threat Analysis
di: Abtahi, Farhad, et al.
Pubblicazione: (2025)

PathSeeker: Exploring LLM Security Vulnerabilities with a Reinforcement Learning-Based Jailbreak Approach
di: Lin, Zhihao, et al.
Pubblicazione: (2024)

Bridging AI and Software Security: A Comparative Vulnerability Assessment of LLM Agent Deployment Paradigms
di: Gasmi, Tarek, et al.
Pubblicazione: (2025)

JADES: A Universal Framework for Jailbreak Assessment via Decompositional Scoring
di: Chu, Junjie, et al.
Pubblicazione: (2025)

Agent-Fence: Mapping Security Vulnerabilities Across Deep Research Agents
di: Puppala, Sai, et al.
Pubblicazione: (2026)

STRIDE-AI: A Threat Modeling Framework for Generative AI Security Assessment
di: Cyrille, Tsafac Nkombong Regine, et al.
Pubblicazione: (2026)

Penetration Testing of Agentic AI: A Comparative Security Analysis Across Models and Frameworks
di: Nguyen, Viet K., et al.
Pubblicazione: (2025)

Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems
di: Si-ahmed, Ayoub, et al.
Pubblicazione: (2024)

PACEbench: A Framework for Evaluating Practical AI Cyber-Exploitation Capabilities
di: Liu, Zicheng, et al.
Pubblicazione: (2025)

Privacy-Preserving AI for Encrypted Medical Imaging: A Framework for Secure Diagnosis and Learning
di: Siam, Abdullah Al, et al.
Pubblicazione: (2025)

Privacy and Security Threat for OpenAI GPTs
di: Wenying, Wei, et al.
Pubblicazione: (2025)

Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards
di: Hammadia, Taha, et al.
Pubblicazione: (2026)

Quantifying Security Vulnerabilities: A Metric-Driven Security Analysis of Gaps in Current AI Standards
di: Madhavan, Keerthana, et al.
Pubblicazione: (2025)

Medical MLLM is Vulnerable: Cross-Modality Jailbreak and Mismatched Attacks on Medical Multimodal Large Language Models
di: Huang, Xijie, et al.
Pubblicazione: (2024)

AIAuditTrack: A Framework for AI Security system
di: Luo, Zixun, et al.
Pubblicazione: (2025)

CIA+TA Risk Assessment for AI Reasoning Vulnerabilities
di: Aydin, Yuksel
Pubblicazione: (2025)

VADER: A Human-Evaluated Benchmark for Vulnerability Assessment, Detection, Explanation, and Remediation
di: Liu, Ethan TS., et al.
Pubblicazione: (2025)

What Breaks Embodied AI Security:LLM Vulnerabilities, CPS Flaws,or Something Else?
di: Ma, Boyang, et al.
Pubblicazione: (2026)

SoK: Security and Privacy of AI Agents for Blockchain
di: Romandini, Nicolò, et al.
Pubblicazione: (2025)

AgentSCOPE: Evaluating Contextual Privacy Across Agentic Workflows
di: Ngong, Ivoline C., et al.
Pubblicazione: (2026)

Evolving Security in LLMs: A Study of Jailbreak Attacks and Defenses
di: Shang, Zhengchun, et al.
Pubblicazione: (2025)

Jailbreaking and Mitigation of Vulnerabilities in Large Language Models
di: Peng, Benji, et al.
Pubblicazione: (2024)

Fortify Your Foundations: Practical Privacy and Security for Foundation Model Deployments In The Cloud
di: Chrapek, Marcin, et al.
Pubblicazione: (2024)

Amplified Vulnerabilities: Structured Jailbreak Attacks on LLM-based Multi-Agent Debate
di: Qi, Senmao, et al.
Pubblicazione: (2025)

Data Lineage Inference: Uncovering Privacy Vulnerabilities of Dataset Pruning
di: Li, Qi, et al.
Pubblicazione: (2024)

A Security Analysis of the OpenClaw AI Agent Framework
di: Suwansathit, Surada, et al.
Pubblicazione: (2026)

A Comparative Evaluation of AI Agent Security Guardrails
di: Li, Qi, et al.
Pubblicazione: (2026)

Automatic Jailbreaking of the Text-to-Image Generative AI Systems
di: Kim, Minseon, et al.
Pubblicazione: (2024)

Towards Robust and Secure Embodied AI: A Survey on Vulnerabilities and Attacks
di: Xing, Wenpeng, et al.
Pubblicazione: (2025)

Offensive Security for AI Systems: Concepts, Practices, and Applications
di: Harguess, Josh, et al.
Pubblicazione: (2025)

SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code
di: Li, Xinghang, et al.
Pubblicazione: (2025)

Towards Secure and Private AI: A Framework for Decentralized Inference
di: Zhang, Hongyang, et al.
Pubblicazione: (2024)

SoK: Evaluating Jailbreak Guardrails for Large Language Models
di: Wang, Xunguang, et al.
Pubblicazione: (2025)

Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training
di: Khan, Tanveer, et al.
Pubblicazione: (2024)

The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models
di: Wu, Zihui, et al.
Pubblicazione: (2024)

Can Small Language Models Reliably Resist Jailbreak Attacks? A Comprehensive Evaluation
di: Zhang, Wenhui, et al.
Pubblicazione: (2025)

LLMs Can Defend Themselves Against Jailbreaking in a Practical Manner: A Vision Paper
di: Wu, Daoyuan, et al.
Pubblicazione: (2024)

DMN: A Compositional Framework for Jailbreaking Multimodal LLMs with Multi-Image Inputs
di: Xu, Wenzhuo, et al.
Pubblicazione: (2026)