2,529+ academic papers on AI security, attacks, and defenses
Showing 261–280 of 312 papers
Clear filtersPetar Radanliev
Problem Space: AI Vulnerabilities and Quantum Threats Generative AI vulnerabilities: model inversion, data poisoning, adversarial inputs. Quantum...
Yushi Yang, Shreyansh Padarha, Andrew Lee +1 more
Agentic reinforcement learning (RL) trains large language models to autonomously call tools during reasoning, with search as the most common...
Elias Hossain, Swayamjit Saha, Somshubhra Roy +1 more
Even when prompts and parameters are secured, transformer language models remain vulnerable because their key-value (KV) cache during inference...
Jie Zhang, Meng Ding, Yang Liu +2 more
We present a novel approach for attacking black-box large language models (LLMs) by exploiting their ability to express confidence in natural...
Asmita Mohanty, Gezheng Kang, Lei Gao +1 more
Large Language Models (LLMs) have demonstrated strong performance across diverse tasks, but fine-tuning them typically relies on cloud-based,...
Sarah Egler, John Schulman, Nicholas Carlini
Large Language Model (LLM) providers expose fine-tuning APIs that let end users fine-tune their frontier LLMs. Unfortunately, it has been shown that...
Andrew Zhao, Reshmi Ghosh, Vitor Carvalho +4 more
Large language model (LLM) systems increasingly power everyday AI applications such as chatbots, computer-use assistants, and autonomous robots,...
Fanchao Meng, Jiaping Gui, Yunbo Li +1 more
Modern Network Intrusion Detection Systems generate vast volumes of low-level alerts, yet these outputs remain semantically fragmented, requiring...
Jianzhu Yao, Hongxu Su, Taobo Liao +4 more
Neural networks increasingly run on hardware outside the user's control (cloud GPUs, inference marketplaces). Yet ML-as-a-Service reveals little...
Daniel Pulido-Cortázar, Daniel Gibert, Felip Manyà
Over the last decade, machine learning has been extensively applied to identify malicious Android applications. However, such approaches remain...
Deeksha Hareesha Kulal, Chidozie Princewill Arannonu, Afsah Anwar +2 more
Phishing remains a critical cybersecurity threat, especially with the advent of large language models (LLMs) capable of generating highly convincing...
Sean Oesch, Jack Hutchins, Luke Koch +1 more
In living off the land attacks, malicious actors use legitimate tools and processes already present on a system to avoid detection. In this paper, we...
Rui Xu, Jiawei Chen, Zhaoxia Yin +2 more
The widespread use of large language models (LLMs) and open-source code has raised ethical and security concerns regarding the distribution and...
Zaixi Zhang, Souradip Chakraborty, Amrit Singh Bedi +16 more
The rapid adoption of generative artificial intelligence (GenAI) in the biosciences is transforming biotechnology, medicine, and synthetic biology....
Tiarnaigh Downey-Webb, Olamide Jogunola, Oluwaseun Ajao
This paper presents a systematic security assessment of four prominent Large Language Models (LLMs) against diverse adversarial attack vectors. We...
Brandon Lit, Edward Crowder, Daniel Vogel +1 more
AI chatbots are an emerging security attack vector, vulnerable to threats such as prompt injection, and rogue chatbot creation. When deployed in...
Abhishek K. Mishra, Antoine Boutet, Lucas Magnana
Large Language Models (LLMs) are increasingly deployed across multilingual applications that handle sensitive data, yet their scale and linguistic...
Aofan Liu, Lulu Tang
Vision-Language Models (VLMs) have garnered significant attention for their remarkable ability to interpret and generate multimodal content. However,...
Jiyang Qiu, Xinbei Ma, Yunqing Xu +2 more
The rapid deployment of large language model (LLM)-based agents in real-world applications has raised serious concerns about their trustworthiness....
Tavish McDonald, Bo Lei, Stanislav Fort +2 more
Models are susceptible to adversarially out-of-distribution (OOD) data despite large training-compute investments into their robustification. Zaremba...
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