2,583+ academic papers on AI security, attacks, and defenses
Showing 541–560 of 658 papers
Clear filtersLinzhi Chen, Yang Sun, Hongru Wei +1 more
Low-Rank Adaptation (LoRA) has emerged as an efficient method for fine-tuning large language models (LLMs) and is widely adopted within the...
Sameera K. M., Serena Nicolazzo, Antonino Nocera +2 more
Federated Learning (FL) has recently emerged as a revolutionary approach to collaborative training Machine Learning models. In particular, it enables...
Liming Lu, Xiang Gu, Junyu Huang +5 more
Large Language Models (LLMs) are increasingly used in agentic systems, where their interactions with diverse tools and environments create complex,...
Akshaj Prashanth Rao, Advait Singh, Saumya Kumaar Saksena +1 more
Prompt injection and jailbreaking attacks pose persistent security challenges to large language model (LLM)-based systems. We present PromptScreen,...
Zhang Wei, Peilu Hu, Zhenyuan Wei +16 more
The increasing deployment of large language models (LLMs) in safety-critical applications raises fundamental challenges in systematically evaluating...
Jianyi Zhang, Shizhao Liu, Ziyin Zhou +1 more
The rapid advancement of large language models (LLMs) has intensified concerns about the robustness of their safety alignment. While existing...
Zehao Liu, Xi Lin
Large Language Models (LLMs) have gained considerable popularity and protected by increasingly sophisticated safety mechanisms. However, jailbreak...
Huixin Zhan
Genomic Foundation Models (GFMs), such as Evolutionary Scale Modeling (ESM), have demonstrated remarkable success in variant effect prediction....
Kai Hu, Abhinav Aggarwal, Mehran Khodabandeh +6 more
This paper introduces Jailbreak-Zero, a novel red teaming methodology that shifts the paradigm of Large Language Model (LLM) safety evaluation from a...
Xiao Li, Yue Li, Hao Wu +4 more
As large language models (LLMs) are increasingly adopted for code vulnerability detection, their reliability and robustness across diverse...
Safwan Shaheer, G. M. Refatul Islam, Mohammad Rafid Hamid +1 more
In this fast-evolving area of LLMs, our paper discusses the significant security risk presented by prompt injection attacks. It focuses on small...
Hao Li, Yubing Ren, Yanan Cao +4 more
With the rapid development of cloud-based services, large language models (LLMs) have become increasingly accessible through various web platforms....
Joao Queiroz
Recent evidence shows that the versification of prompts constitutes a highly effective adversarial mechanism against aligned LLMs. The study...
Pablo Montaña-Fernández, Ines Ortega-Fernandez
Federated Learning is a machine learning setting that reduces direct data exposure, improving the privacy guarantees of machine learning models. Yet,...
Xingfu Zhou, Pengfei Wang
Large Language Model (LLM) agents relying on external retrieval are increasingly deployed in high-stakes environments. While existing adversarial...
Yunhao Yao, Zhiqiang Wang, Haoran Cheng +3 more
The evolution of Large Language Models (LLMs) into Agentic AI has established the Model Context Protocol (MCP) as the standard for connecting...
Shuxin Zhao, Bo Lang, Nan Xiao +1 more
Object detection models deployed in real-world applications such as autonomous driving face serious threats from backdoor attacks. Despite their...
Sabrine Ennaji, Elhadj Benkhelifa, Luigi Vincenzo Mancini
Machine learning based intrusion detection systems are increasingly targeted by black box adversarial attacks, where attackers craft evasive inputs...
Karina Chichifoi, Fabio Merizzi, Michele Colajanni
Deep learning and federated learning (FL) are becoming powerful partners for next-generation weather forecasting. Deep learning enables...
Md. Hasib Ur Rahman
As Large Language Models (LLMs) become ubiquitous, the challenge of securing them against adversarial "jailbreaking" attacks has intensified. Current...
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