2,077+ academic papers on AI security, attacks, and defenses
Showing 241–259 of 259 papers
Clear filtersDalal Alharthi, Ivan Roberto Kawaminami Garcia
Large language models have gained widespread prominence, yet their vulnerability to prompt injection and other adversarial attacks remains a critical...
Samar Fares, Nurbek Tastan, Noor Hussein +1 more
Generative models can generate photorealistic images at scale. This raises urgent concerns about the ability to detect synthetically generated images...
Luis Burbano, Diego Ortiz, Qi Sun +5 more
Embodied Artificial Intelligence (AI) promises to handle edge cases in robotic vehicle systems where data is scarce by using common-sense reasoning...
Anshul Nasery, Edoardo Contente, Alkin Kaz +2 more
Model fingerprinting has emerged as a promising paradigm for claiming model ownership. However, robustness evaluations of these schemes have mostly...
Firas Ben Hmida, Abderrahmen Amich, Ata Kaboudi +1 more
Deep neural networks (DNNs) are increasingly being deployed in high-stakes applications, from self-driving cars to biometric authentication. However,...
Marco Zimmerli, Andreas Plesner, Till Aczel +1 more
Deep neural networks remain vulnerable to adversarial examples despite advances in architectures and training paradigms. We investigate how training...
Dennis Jacob, Emad Alghamdi, Zhanhao Hu +2 more
Large language models (LLMs) have become increasingly popular due to their ability to interact with unstructured content. As such, LLMs are now a key...
Thomas Fargues, Ye Dong, Tianwei Zhang +1 more
The rapid growth of Large Language Models (LLMs) has highlighted the pressing need for reliable mechanisms to verify content ownership and ensure...
Yuzhen Long, Songze Li
Autonomous driving systems increasingly rely on multi-agent architectures powered by large language models (LLMs), where specialized agents...
Jongwook Han, Jongwon Lim, Injin Kong +1 more
Large language models can express values in two main ways: (1) intrinsic expression, reflecting the model's inherent values learned during training,...
Zihao Zhu, Xinyu Wu, Gehan Hu +3 more
Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in complex problem-solving through Chain-of-Thought (CoT) reasoning. However,...
Han Yan, Zheyuan Liu, Meng Jiang
With the rapid advancement of large language models, Machine Unlearning has emerged to address growing concerns around user privacy, copyright...
Jeongyeon Hwang, Sangdon Park, Jungseul Ok
Watermarking offers a promising solution for detecting LLM-generated content, yet its robustness under realistic query-free (black-box) evasion...
Xingyu Li, Juefei Pu, Yifan Wu +13 more
Open-source software projects are foundational to modern software ecosystems, with the Linux kernel standing out as a critical exemplar due to its...
David Benfield, Stefano Coniglio, Phan Tu Vuong +1 more
Adversarial machine learning concerns situations in which learners face attacks from active adversaries. Such scenarios arise in applications such as...
Miao Yu, Zhenhong Zhou, Moayad Aloqaily +5 more
Fine-tuned Large Language Models (LLMs) are vulnerable to backdoor attacks through data poisoning, yet the internal mechanisms governing these...
Jiahao Huo, Shuliang Liu, Bin Wang +5 more
Semantic-level watermarking (SWM) for large language models (LLMs) enhances watermarking robustness against text modifications and paraphrasing...
Anh Tu Ngo, Anupam Chattopadhyay, Subhamoy Maitra
In this paper we show that cryptographic backdoors in a neural network (NN) can be highly effective in two directions, namely mounting the attacks as...
Xiaofan Li, Xing Gao
In recent years, various software supply chain (SSC) attacks have posed significant risks to the global community. Severe consequences may arise if...
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