2,077+ academic papers on AI security, attacks, and defenses
Showing 561–580 of 965 papers
Clear filtersAink Acrie Soe Thein, Nikolaos Pitropakis, Pavlos Papadopoulos +2 more
With the adoption of multiple digital devices in everyday life, the cyber-attack surface has increased. Adversaries are continuously exploring new...
Xinye Cao, Yihan Lin, Guoshun Nan +9 more
Zero-Touch Networks (ZTNs) represent a transformative paradigm toward fully automated and intelligent network management, providing the scalability...
Sohely Jahan, Ruimin Sun
As medical large language models (LLMs) become increasingly integrated into clinical workflows, concerns around alignment robustness, and safety are...
Miranda Christ, Noah Golowich, Sam Gunn +2 more
Watermarks are an essential tool for identifying AI-generated content. Recently, Christ and Gunn (CRYPTO '24) introduced pseudorandom...
Mohamed Elmahallawy, Sanjay Madria, Samuel Frimpong
Underground mining operations depend on sensor networks to monitor critical parameters such as temperature, gas concentration, and miner movement,...
Botao 'Amber' Hu, Bangdao Chen
The emerging "agentic web" envisions large populations of autonomous agents coordinating, transacting, and delegating across open networks. Yet many...
Gary Ackerman, Zachary Kallenborn, Anna Wetzel +7 more
The potential for rapidly-evolving frontier artificial intelligence (AI) models, especially large language models (LLMs), to facilitate bioterrorism...
Xiaoqi Li, Lei Xie, Wenkai Li +1 more
In the case of upgrading smart contracts on blockchain systems, it is essential to consider the continuity of upgrades and subsequent maintenance. In...
Shiva Gaire, Srijan Gyawali, Saroj Mishra +3 more
The Model Context Protocol (MCP) has emerged as the de facto standard for connecting Large Language Models (LLMs) to external data and tools,...
Md Nazmul Haque, Elizabeth Lin, Lawrence Arkoh +2 more
Large Language Models for code (LLMs4Code) are increasingly used to generate software artifacts, including library and package recommendations in...
Lukas Johannes Möller
The escalating sophistication and variety of cyber threats have rendered static honeypots inadequate, necessitating adaptive, intelligence-driven...
Jordan Taylor, Sid Black, Dillon Bowen +10 more
Future AI systems could conceal their capabilities ('sandbagging') during evaluations, potentially misleading developers and auditors. We...
JV Roig
We investigate how large language models (LLMs) fail when operating as autonomous agents with tool-use capabilities. Using the Kamiwaza Agentic Merit...
Qiwei Tian, Chenhao Lin, Zhengyu Zhao +1 more
To address the trade-off between robustness and performance for robust VLM, we observe that function words could incur vulnerability of VLMs against...
Fenghua Weng, Chaochao Lu, Xia Hu +2 more
As multimodal reasoning improves the overall capabilities of Large Vision Language Models (LVLMs), recent studies have begun to explore...
George Mikros
Large language models (LLMs) present a dual challenge for forensic linguistics. They serve as powerful analytical tools enabling scalable corpus...
Guanquan Shi, Haohua Du, Zhiqiang Wang +4 more
Large Language Models (LLMs) are evolving into autonomous agents capable of executing complex workflows via standardized protocols (e.g., MCP)....
Wenjie Zhang, Yun Lin, Chun Fung Amos Kwok +5 more
Detecting the anomalies of web applications, important infrastructures for running modern companies and governments, is crucial for providing...
Xiaoqi Li, Hailu Kuang, Wenkai Li +2 more
Traditional approaches for smart contract analysis often rely on intermediate representations such as abstract syntax trees, control-flow graphs, or...
Sima Jafarikhah, Daniel Thompson, Eva Deans +2 more
Manual vulnerability scoring, such as assigning Common Vulnerability Scoring System (CVSS) scores, is a resource-intensive process that is often...
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