2,077+ academic papers on AI security, attacks, and defenses
Showing 261–280 of 522 papers
Clear filtersOmer Gazit, Yael Itzhakev, Yuval Elovici +1 more
Radio frequency (RF) based systems are increasingly used to detect drones by analyzing their RF signal patterns, converting them into spectrogram...
Linzhi 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...
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,...
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...
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...
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...
Yixin Tan, Zhe Yu, Jun Sakuma
Finetuning pretrained large language models (LLMs) has become the standard paradigm for developing downstream applications. However, its security...
Safwan Shaheer, G. M. Refatul Islam, Mohammad Rafid Hamid +3 more
Prompt injection attacks can compromise the security and stability of critical systems, from infrastructure to large web applications. This work...
Peichun Hua, Hao Li, Shanghao Shi +2 more
Large Vision-Language Models (LVLMs) are vulnerable to a growing array of multimodal jailbreak attacks, necessitating defenses that are both...
Jie Ma, Junqing Zhang, Guanxiong Shen +2 more
Radio frequency fingerprint identification (RFFI) is an emerging technique for the lightweight authentication of wireless Internet of things (IoT)...
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