2,560+ academic papers on AI security, attacks, and defenses
Showing 641–660 of 982 papers
Clear filtersFan Yang
Large Language Models (LLMs) have demonstrated exceptional performance across various tasks, but their security vulnerabilities can be exploited by...
Jinbo Liu, Defu Cao, Yifei Wei +6 more
Graph topology is a fundamental determinant of memory leakage in multi-agent LLM systems, yet its effects remain poorly quantified. We introduce MAMA...
Itay Yona, Amir Sarid, Michael Karasik +1 more
We introduce $\textbf{Doublespeak}$, a simple in-context representation hijacking attack against large language models (LLMs). The attack works by...
Hanxiu Zhang, Yue Zheng
The protection of Intellectual Property (IP) in Large Language Models (LLMs) represents a critical challenge in contemporary AI research. While...
Jun Leng, Yu Liu, Litian Zhang +3 more
Large Language Models (LLMs) serve as the backbone of modern AI systems, yet they remain susceptible to adversarial jailbreak attacks. Consequently,...
Thomas Rivasseau
Current research on operator control of Large Language Models improves model robustness against adversarial attacks and misbehavior by training on...
Yuan Xiong, Ziqi Miao, Lijun Li +3 more
While Multimodal Large Language Models (MLLMs) show remarkable capabilities, their safety alignments are susceptible to jailbreak attacks. Existing...
Afshin Khadangi, Hanna Marxen, Amir Sartipi +2 more
Frontier large language models (LLMs) such as ChatGPT, Grok and Gemini are increasingly used for mental-health support with anxiety, trauma and...
Ziyi Tong, Feifei Sun, Le Minh Nguyen
Large Multimodal Language Models (MLLMs) are emerging as one of the foundational tools in an expanding range of applications. Consequently,...
Yuanhe Zhang, Weiliu Wang, Zhenhong Zhou +5 more
Large Language Model (LLM)-based agents have demonstrated remarkable capabilities in reasoning, planning, and tool usage. The recently proposed Model...
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1 more
Traffic classification (TC) plays a critical role in cybersecurity, particularly in IoT and embedded contexts, where inspection must often occur...
Zixia Wang, Gaojie Jin, Jia Hu +1 more
Recent advancements in Large Language Models (LLMs) have led to their widespread adoption in daily applications. Despite their impressive...
Alexander Boyd, Franz Nowak, David Hyland +2 more
World models have been recently proposed as sandbox environments in which AI agents can be trained and evaluated before deployment. Although...
Aaron Sandoval, Cody Rushing
The field of AI Control seeks to develop robust control protocols, deployment safeguards for untrusted AI which may be intentionally subversive....
Haowei Fu, Bo Ni, Han Xu +3 more
Retrieval-Augmented Generation (RAG) and Supervised Finetuning (SFT) have become the predominant paradigms for equipping Large Language Models (LLMs)...
Adeela Bashir, The Anh han, Zia Ush Shamszaman
The integration of large language models (LLMs) into healthcare IoT systems promises faster decisions and improved medical support. LLMs are also...
Omar Farooq Khan Suri, John McCrae
Large Language Models (LLMs) are increasingly being deployed in real-world applications, but their flexibility exposes them to prompt injection...
Zihao Wang, Kar Wai Fok, Vrizlynn L. L. Thing
Multi-modal large language models (MLLMs), capable of processing text, images, and audio, have been widely adopted in various AI applications....
Mintong Kang, Chong Xiang, Sanjay Kariyappa +3 more
Indirect prompt injection attacks (IPIAs), where large language models (LLMs) follow malicious instructions hidden in input data, pose a critical...
Hao Wu, Prateek Saxena
This paper explores attacks and defenses on vector databases in retrieval-augmented generation (RAG) systems. Prior work on knowledge poisoning...
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