2,529+ academic papers on AI security, attacks, and defenses
Showing 1–20 of 106 papers
Clear filtersJoel Rorseth, Parke Godfrey, Lukasz Golab +2 more
This paper demonstrates RUBEN, an interactive tool for discovering minimal rules to explain the outputs of retrieval-augmented large language models...
Michael A. Riegler, Inga Strümke
We present swarm-attack, an open-source adversarial testing framework in which multiple lightweight LLM agents coordinate through shared memory,...
Chengjie Wang, Jingzheng Wu, Xiang Ling +2 more
Large language models (LLMs) are now largely involved in software development workflows, and the code they generate routinely includes third-party...
Kerri Prinos, Lilianne Brush, Cameron Denton +5 more
Agentic systems involved in high-stake decision-making under adversarial pressure need formal guarantees not offered by existing approaches....
Mingming Zha, Xiaofeng Wang
Autonomous LLM agents operate as long-running processes with persistent workspaces, memory files, scheduled task state, and messaging integrations....
Neha Nagaraja, Hayretdin Bahsi, Carlo R. da Cunha
As large language models are integrated into autonomous robotic systems for task planning and control, compromised inputs or unsafe model outputs can...
Kato Mivule
This paper extends the Classification Error Gauge (x-CEG) framework, originally developed for measuring the privacy-utility trade-off in tabular...
Mikko Lempinen, Joni Kemppainen, Niklas Raesalmi
As artificial intelligence (AI) systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of...
Yuan Fang, Yiming Luo, Aimin Zhou +1 more
Ensuring the safety of large language models (LLMs) requires robust red teaming, yet the systematic synthesis of high-quality toxic data remains...
Shangkun Che, Silin Du, Ge Gao
The widespread use of Large Language Models (LLMs) in text generation has raised increasing concerns about intellectual property disputes....
Hengkai Ye, Zhechang Zhang, Jinyuan Jia +1 more
Large language models (LLMs) increasingly rely on external tools to perform time-sensitive tasks and real-world actions. While tool integration...
Yen-Shan Chen, Sian-Yao Huang, Cheng-Lin Yang +1 more
As large language models (LLMs) evolve from static chatbots into autonomous agents, the primary vulnerability surface shifts from final outputs to...
Yinghan Hou, Zongyou Yang
OpenClaw's ClawHub marketplace hosts over 13,000 community-contributed agent skills, and between 13% and 26% of them contain security vulnerabilities...
Shaofei Huang, Christopher M. Poskitt, Lwin Khin Shar
Cyber-physical systems often contend with incomplete architectural documentation or outdated information resulting from legacy technologies,...
Anes Abdennebi, Nadjia Kara, Laaziz Lahlou +1 more
Modern Security Operations Centers struggle with alert fatigue, fragmented tooling, and limited cross-source event correlation. Challenges that...
Wuyang Zhang, Shichao Pei
Tool-use large language model (LLM) agents are increasingly deployed to support sensitive workflows, relying on tool calls for retrieval, external...
Jiling Zhou, Aisvarya Adeseye, Seppo Virtanen +2 more
Chain-of-Thought (CoT) prompting has been used to enhance the reasoning capability of LLMs. However, its reliability in security-sensitive analytical...
Fariha Tanjim Shifat, Hariswar Baburaj, Ce Zhou +2 more
Large language models (LLMs) are increasingly embedded in open-source software (OSS) ecosystems, creating complex interactions among natural language...
Jihoon Jeong
AI models of equivalent capability can exhibit fundamentally different behavioral patterns, yet no standardized instrument exists to measure these...
Aymen Bouferroum, Valeria Loscri, Abderrahim Benslimane
The Industrial Internet of Things (IIoT) introduces significant security challenges as resource-constrained devices become increasingly integrated...
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