2,529+ academic papers on AI security, attacks, and defenses
Showing 161–180 of 212 papers
Clear filtersRasmus Erlemann, Charles Colyer Morris, Sanjyot Sathe
The emergence of large-scale quantum computing threatens widely deployed public-key cryptographic systems, creating an urgent need for...
Xiangdong Hu, Yangyang Jiang, Qin Hu +1 more
Multimodal Large Language Models (MLLMs) have become widely deployed, yet their safety alignment remains fragile under adversarial inputs. Previous...
Sofie Goethals, Foster Provost, João Sedoc
As generative AI systems become integrated into real-world applications, organizations increasingly need to be able to understand and interpret their...
Gongao Zhang, Haijiang Zeng, Lu Jiang
Financial institutions and regulators require systems that integrate heterogeneous data to assess risks from stock fluctuations to systemic...
Md Ajoad Hasan, Dipayan Saha, Khan Thamid Hasan +5 more
The growing complexity of modern system-on-chip (SoC) and IP designs is making security assurance difficult day by day. One of the fundamental steps...
Arina Kharlamova, Youcheng Sun, Ting Yu
Private macOS frameworks underpin critical services and daemons but remain undocumented and distributed only as stripped binaries, complicating...
Xin 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...
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