2,077+ academic papers on AI security, attacks, and defenses
Showing 61–73 of 73 papers
Clear filtersChenYu Wu, Yi Wang, Yang Liao
Large language models (LLMs) are increasingly vulnerable to multi-turn jailbreak attacks, where adversaries iteratively elicit harmful behaviors that...
Zixuan Liu, Yi Zhao, Zhuotao Liu +4 more
Machine Learning (ML)-based malicious traffic detection is a promising security paradigm. It outperforms rule-based traditional detection by...
Caelin Kaplan, Alexander Warnecke, Neil Archibald
AI models are being increasingly integrated into real-world systems, raising significant concerns about their safety and security. Consequently, AI...
Zicheng Liu, Lige Huang, Jie Zhang +3 more
The increasing autonomy of Large Language Models (LLMs) necessitates a rigorous evaluation of their potential to aid in cyber offense. Existing...
Pengyu Zhu, Lijun Li, Yaxing Lyu +3 more
LLM-based multi-agent systems (MAS) demonstrate increasing integration into next-generation applications, but their safety in backdoor attacks...
Hyeseon An, Shinwoo Park, Suyeon Woo +1 more
The promise of LLM watermarking rests on a core assumption that a specific watermark proves authorship by a specific model. We demonstrate that this...
Dennis Rall, Bernhard Bauer, Mohit Mittal +1 more
Large language models (LLMs) are now routinely used to autonomously execute complex tasks, from natural language processing to dynamic workflows like...
Jonathan Sneh, Ruomei Yan, Jialin Yu +6 more
As LLMs increasingly power agents that interact with external tools, tool use has become an essential mechanism for extending their capabilities....
Shoumik Saha, Jifan Chen, Sam Mayers +3 more
Code-capable large language model (LLM) agents are increasingly embedded into software engineering workflows where they can read, write, and execute...
Jing-Jing Li, Jianfeng He, Chao Shang +6 more
As LLMs advance into autonomous agents with tool-use capabilities, they introduce security challenges that extend beyond traditional content-based...
Petar Radanliev
This study presents a structured approach to evaluating vulnerabilities within quantum cryptographic protocols, focusing on the BB84 quantum key...
Ping He, Changjiang Li, Binbin Zhao +2 more
The remarkable capability of large language models (LLMs) has led to the wide application of LLM-based agents in various domains. To standardize...
Adam Swanda, Amy Chang, Alexander Chen +3 more
The widespread adoption of Large Language Models (LLMs) has revolutionized AI deployment, enabling autonomous and semi-autonomous applications across...
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