2,077+ academic papers on AI security, attacks, and defenses
Showing 121–140 of 226 papers
Clear filtersXin Wang, Yunhao Chen, Juncheng Li +7 more
The rapid integration of Multimodal Large Language Models (MLLMs) into critical applications is increasingly hindered by persistent safety...
Yueyan Dong, Minghui Xu, Qin Hu +5 more
Low-Rank Adaptation (LoRA) has become a popular solution for fine-tuning large language models (LLMs) in federated settings, dramatically reducing...
Vidyut Sriram, Sawan Pandita, Achintya Lakshmanan +2 more
Large Language Models (LLMs) can generate code but often introduce security vulnerabilities, logical inconsistencies, and compilation errors. Prior...
Toqeer Ali Syed, Mishal Ateeq Almutairi, Mahmoud Abdel Moaty
Powerful autonomous systems, which reason, plan, and converse using and between numerous tools and agents, are made possible by Large Language Models...
Armstrong Foundjem, Lionel Nganyewou Tidjon, Leuson Da Silva +1 more
Machine learning (ML) underpins foundation models in finance, healthcare, and critical infrastructure, making them targets for data poisoning, model...
Songze Li, Jiameng Cheng, Yiming Li +2 more
By integrating language understanding with perceptual modalities such as images, multimodal large language models (MLLMs) constitute a critical...
Shaghayegh Shajarian, Kennedy Marsh, James Benson +2 more
Modern networks generate vast, heterogeneous traffic that must be continuously analyzed for security and performance. Traditional network traffic...
Junjun Pan, Yixin Liu, Rui Miao +5 more
Large language model (LLM)-based multi-agent systems (MAS) have shown strong capabilities in solving complex tasks. As MAS become increasingly...
Bin Wang, Wenjie Yu, Yilu Zhong +6 more
Large language models (LLMs) for code generation are becoming integral to modern software development, but their real-world prevalence and security...
Zehao Liu, Xi Lin
Large Language Models (LLMs) have gained considerable popularity and protected by increasingly sophisticated safety mechanisms. However, jailbreak...
Abhivansh Gupta
As LLM-based agents grow more autonomous and multi-modal, ensuring they remain controllable, auditable, and faithful to deployer intent becomes...
Xiao Li, Yue Li, Hao Wu +4 more
As large language models (LLMs) are increasingly adopted for code vulnerability detection, their reliability and robustness across diverse...
Richard Helder Moulton, Austin O'Brien, John D. Hastings
Although large language models (LLMs) are increasingly used in security-critical workflows, practitioners lack quantitative guidance on which...
Viet K. Nguyen, Mohammad I. Husain
Agentic AI introduces security vulnerabilities that traditional LLM safeguards fail to address. Although recent work by Unit 42 at Palo Alto Networks...
Arth Bhardwaj, Sia Godika, Yuvam Loonker
Traditional, centralized security tools often miss adaptive, multi-vector attacks. We present the Multi-Agent LLM Cyber Defense Framework (MALCDF), a...
Dongchao Zhou, Lingyun Ying, Huajun Chai +1 more
JavaScript's widespread adoption has made it an attractive target for malicious attackers who employ sophisticated obfuscation techniques to conceal...
Amy Chang, Tiffany Saade, Sanket Mendapara +2 more
Artificial intelligence (AI) systems are being readily and rapidly adopted, increasingly permeating critical domains: from consumer platforms and...
Shashie Dilhara Batan Arachchige, Benjamin Zi Hao Zhao, Hassan Jameel Asghar +2 more
Large Language Models (LLMs) are often fine-tuned to adapt their general-purpose knowledge to specific tasks and domains such as cyber threat...
Padmeswari Nandiya, Ahmad Mohsin, Ahmed Ibrahim +2 more
Industry 5.0's increasing integration of IT and OT systems is transforming industrial operations but also expanding the cyber-physical attack...
Jinghao Wang, Ping Zhang, Carter Yagemann
Medical Large Language Models (LLMs) are increasingly deployed for clinical decision support across diverse specialties, yet systematic evaluation of...
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