2,077+ academic papers on AI security, attacks, and defenses
Showing 421–440 of 2,031 papers
Clear filtersTianyu Chen, Dongrui Liu, Xia Hu +2 more
Clawdbot is a self-hosted, tool-using personal AI agent with a broad action space spanning local execution and web-mediated workflows, which raises...
Zhenhong Zhou, Yuanhe Zhang, Hongwei Cai +6 more
The Model Context Protocol (MCP) standardizes tool use for LLM-based agents and enable third-party servers. This openness introduces a security...
Matic Korun
We propose a geometric taxonomy of large language model hallucinations based on observable signatures in token embedding cluster structure. By...
Xiaojun Jia, Jie Liao, Simeng Qin +5 more
Agent skills are becoming a core abstraction in coding agents, packaging long-form instructions and auxiliary scripts to extend tool-augmented...
Max Fomin
Detecting prompt injection and jailbreak attacks is critical for deploying LLM-based agents safely. As agents increasingly process untrusted data...
Mario Marín Caballero, Miguel Betancourt Alonso, Daniel Díaz-López +3 more
The most valuable asset of any cloud-based organization is data, which is increasingly exposed to sophisticated cyberattacks. Until recently, the...
Edibe Yilmaz, Kahraman Kostas
The integration of large language models (LLMs) into educational processes introduces significant constraints regarding data privacy and reliability,...
Somnath Banerjee
The overarching research direction of this work is the development of a ''Responsible Intelligence'' framework designed to reconcile the immense...
Yuqi Jia, Ruiqi Wang, Xilong Wang +2 more
Prompt injection attacks insert malicious instructions into an LLM's input to steer it toward an attacker-chosen task instead of the intended one....
Ruomeng Ding, Yifei Pang, He Sun +3 more
Evaluation and alignment pipelines for large language models increasingly rely on LLM-based judges, whose behavior is guided by natural-language...
Haoyu Li, Xijia Che, Yanhao Wang +2 more
Proof-of-Vulnerability (PoV) generation is a critical task in software security, serving as a cornerstone for vulnerability validation, false...
Weiming Song, Xuan Xie, Ruiping Yin
Large language models (LLMs) remain vulnerable to jailbreak prompts that elicit harmful or policy-violating outputs, while many existing defenses...
Mohamed Shaaban, Mohamed Elmahallawy
Federated learning (FL) enables collaborative training across organizational silos without sharing raw data, making it attractive for...
Peng Cheng, Jiucheng Zang, Qingnan Li +6 more
Muon-style optimizers leverage Newton-Schulz (NS) iterations to orthogonalize updates, yielding update geometries that often outperform Adam-series...
Akshat Naik, Jay Culligan, Yarin Gal +4 more
As Large Language Model (LLM) agents become more capable, their coordinated use in the form of multi-agent systems is anticipated to emerge as a...
Anudeep Das, Prach Chantasantitam, Gurjot Singh +3 more
Large language models (LLMs) are increasingly deployed in settings where inducing a bias toward a certain topic can have significant consequences,...
Xu Li, Simon Yu, Minzhou Pan +5 more
LLM-based agents are becoming increasingly capable, yet their safety lags behind. This creates a gap between what agents can do and should do. This...
Yiran Gao, Kim Hammar, Tao Li
Rapidly evolving cyberattacks demand incident response systems that can autonomously learn and adapt to changing threats. Prior work has extensively...
Alfous Tim, Kuniyilh Simi D
The Internet of Things (IoT) systems increasingly depend on continual learning to adapt to non-stationary environments. These environments can...
George Alexandru Adam, Alexander Cui, Edwin Thomas +7 more
While historical considerations surrounding text authenticity revolved primarily around plagiarism, the advent of large language models (LLMs) has...
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