2,560+ academic papers on AI security, attacks, and defenses
Showing 341–360 of 725 papers
Clear filtersSri Durga Sai Sowmya Kadali, Evangelos E. Papalexakis
Jailbreaking large language models (LLMs) has emerged as a critical security challenge with the widespread deployment of conversational AI systems....
Abhishek Saini, Haolin Jiang, Hang Liu
The deployment of large language models (LLMs) on third-party devices requires new ways to protect model intellectual property. While Trusted...
J Alex Corll
Multi-turn prompt injection attacks distribute malicious intent across multiple conversation turns, exploiting the assumption that each turn is...
Shuyu Chang, Haiping Huang, Yanjun Zhang +3 more
Code models are increasingly adopted in software development but remain vulnerable to backdoor attacks via poisoned training data. Existing backdoor...
Qianli Wang, Boyang Ma, Minghui Xu +1 more
LLM agents often rely on Skills to describe available tools and recommended procedures. We study a hidden-comment prompt injection risk in this...
Tri Nguyen, Huy Hoang Bao Le, Lohith Srikanth Pentapalli +2 more
Detecting jailbreak attempts in clinical training large language models (LLMs) requires accurate modeling of linguistic deviations that signal unsafe...
Zhenyu Xu, Victor S. Sheng
Protecting the intellectual property of large language models (LLMs) is a critical challenge due to the proliferation of unauthorized derivative...
Georgios Syros, Evan Rose, Brian Grinstead +4 more
Large language model (LLM) based web agents are increasingly deployed to automate complex online tasks by directly interacting with web sites and...
Kotekar Annapoorna Prabhu, Andrew Gan, Zahra Ghodsi
Machine learning relies on randomness as a fundamental component in various steps such as data sampling, data augmentation, weight initialization,...
Yu Yan, Sheng Sun, Shengjia Cheng +3 more
Vision-Language Models (VLMs) with multimodal reasoning capabilities are high-value attack targets, given their potential for handling complex...
Suraj Ranganath, Atharv Ramesh
AI-text detectors face a critical robustness challenge: adversarial paraphrasing attacks that preserve semantics while evading detection. We...
Suraj Ranganath, Atharv Ramesh
AI-text detectors face a critical robustness challenge: adversarial paraphrasing attacks that preserve semantics while evading detection. We...
Jona te Lintelo, Lichao Wu, Stjepan Picek
The rapid adoption of Mixture-of-Experts (MoE) architectures marks a major shift in the deployment of Large Language Models (LLMs). MoE LLMs improve...
Yanzhang Fu, Zizheng Guo, Jizhou Luo
Score-based query attacks pose a serious threat to deep learning models by crafting adversarial examples (AEs) using only black-box access to model...
Scott Thornton
Hybrid Retrieval-Augmented Generation (RAG) pipelines combine vector similarity search with knowledge graph expansion for multi-hop reasoning. We...
Benjamin Livshits
We argue that when it comes to producing secure code with AI, the prevailing "fighting fire with fire" approach -- using probabilistic AI-based...
Sahar Zargarzadeh, Mohammad Islam
The Internet of Things (IoT) has revolutionized connectivity by linking billions of devices worldwide. However, this rapid expansion has also...
Pengyu Chang, Yixiong Fang, Silin Chen +3 more
Software testing is a critical, yet resource-intensive phase of the software development lifecycle. Over the years, various automated tools have been...
Md Rafi Ur Rashid, MD Sadik Hossain Shanto, Vishnu Asutosh Dasu +1 more
Vision-Language Models (VLMs) are now a core part of modern AI. Recent work proposed several visual jailbreak attacks using single/ holistic images....
Minbeom Kim, Mihir Parmar, Phillip Wallis +5 more
AI agents equipped with tool-calling capabilities are susceptible to Indirect Prompt Injection (IPI) attacks. In this attack scenario, malicious...
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