2,077+ academic papers on AI security, attacks, and defenses
Showing 581–600 of 965 papers
Clear filtersZhibo Liang, Tianze Hu, Zaiye Chen +1 more
Autonomous Large Language Model (LLM) agents exhibit significant vulnerability to Indirect Prompt Injection (IPI) attacks. These attacks hijack agent...
Donghang Duan, Xu Zheng, Yuefeng He +3 more
Current LLM-based text anonymization frameworks usually rely on remote API services from powerful LLMs, which creates an inherent privacy paradox:...
Jehyeok Yeon, Federico Cinus, Yifan Wu +1 more
Large language models (LLMs) face critical safety challenges, as they can be manipulated to generate harmful content through adversarial prompts and...
Arush Sachdeva, Rajendraprasad Saravanan, Gargi Sarkar +2 more
Cybercrime increasingly exploits human cognitive biases in addition to technical vulnerabilities, yet most existing analytical frameworks focus...
Xianzong Wu, Xiaohong Li, Lili Quan +1 more
Large language models(LLMs) are increasingly expanding their real-world applications across domains, e.g., question answering, autonomous driving,...
Mehrab Hosain, Sabbir Alom Shuvo, Matthew Ogbe +4 more
The modern web stack, which is dominated by browser-based applications and API-first backends, now operates under an adversarial equilibrium where...
Cheng Cheng, Jinqiu Yang
Code-focused Large Language Models (LLMs), such as CodeX and Star-Coder, have demonstrated remarkable capabilities in enhancing developer...
Sheng Liu, Panos Papadimitratos
Federated Learning (FL) has drawn the attention of the Intelligent Transportation Systems (ITS) community. FL can train various models for ITS tasks,...
Jason Vega, Gagandeep Singh
A frustratingly easy technique known as the prefilling attack has been shown to effectively circumvent the safety alignment of frontier LLMs by...
Jiale Zhao, Xing Mou, Jinlin Wu +7 more
Medical Multimodal Large Language Models (Medical MLLMs) have achieved remarkable progress in specialized medical tasks; however, research into their...
Ashish Hooda, Mihai Christodorescu, Chuangang Ren +3 more
Machine learning (ML) models for code clone detection determine whether two pieces of code are semantically equivalent, which in turn is a key...
Wei Zhao, Zhe Li, Jun Sun
Large Language Models (LLMs) exhibit remarkable capabilities but remain vulnerable to adversarial manipulations such as jailbreaking, where crafted...
Eranga Bandara, Amin Hass, Ross Gore +8 more
AI agent-based systems are becoming increasingly integral to modern software architectures, enabling autonomous decision-making, dynamic task...
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...
Chenlin Xu, Lei Zhang, Lituan Wang +5 more
Due to the scarcity of annotated data and the substantial computational costs of model, conventional tuning methods in medical image segmentation...
Biagio Montaruli, Luca Compagna, Serena Elisa Ponta +1 more
The rise of supply chain attacks via malicious Python packages demands robust detection solutions. Current approaches, however, overlook two critical...
Yizhou Zhao, Zhiwei Steven Wu, Adam Block
Watermarking aims to embed hidden signals in generated text that can be reliably detected when given access to a secret key. Open-weight language...
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...
Tengyun Ma, Jiaqi Yao, Daojing He +4 more
Large Language Models (LLMs) have emerged as powerful tools for diverse applications. However, their uniform token processing paradigm introduces...
Hanxiu Zhang, Yue Zheng
The protection of Intellectual Property (IP) in Large Language Models (LLMs) represents a critical challenge in contemporary AI research. While...
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