2,560+ academic papers on AI security, attacks, and defenses
Showing 401–420 of 725 papers
Clear filtersHicham Eddoubi, Umar Faruk Abdullahi, Fadi Hassan
Large Language Models (LLMs) have seen widespread adoption across multiple domains, creating an urgent need for robust safety alignment mechanisms....
Matthew P. Lad, Louisa Conwill, Megan Levis Scheirer
With the rapid growth of Large Language Models (LLMs), criticism of their societal impact has also grown. Work in Responsible AI (RAI) has focused on...
Blake Bullwinkel, Giorgio Severi, Keegan Hines +3 more
Detecting whether a model has been poisoned is a longstanding problem in AI security. In this work, we present a practical scanner for identifying...
Xiaozuo Shen, Yifei Cai, Rui Ning +2 more
The widespread adoption of Vision Transformers (ViTs) elevates supply-chain risk on third-party model hubs, where an adversary can implant backdoors...
Nirab Hossain, Pablo Moriano
Modern vehicles rely on electronic control units (ECUs) interconnected through the Controller Area Network (CAN), making in-vehicle communication a...
Patrick Cooper, Alireza Nadali, Ashutosh Trivedi +1 more
Large language models (LLMs) are known to exhibit brittle behavior under adversarial prompts and jailbreak attacks, even after extensive alignment...
Samuel Nellessen, Tal Kachman
The evolution of large language models into autonomous agents introduces adversarial failures that exploit legitimate tool privileges, transforming...
Ching-Yun Ko, Pin-Yu Chen
Modern artificial intelligence (AI) models are deployed on inference engines to optimize runtime efficiency and resource allocation, particularly for...
Pengfei He, Ash Fox, Lesly Miculicich +7 more
Large language models (LLMs) have shown promise in assisting cybersecurity tasks, yet existing approaches struggle with automatic vulnerability...
Jiayao Wang, Yang Song, Zhendong Zhao +5 more
Federated self-supervised learning (FSSL) enables collaborative training of self-supervised representation models without sharing raw unlabeled data....
Mingrui Liu, Sixiao Zhang, Cheng Long +1 more
Large Language Models (LLMs) are increasingly vulnerable to Prompt Injection (PI) attacks, where adversarial instructions hidden within retrieved...
Pengyu Li, Lingling Zhang, Zhitao Gao +5 more
While Large Language Models (LLMs) have achieved remarkable capabilities, they unintentionally memorize sensitive data, posing critical privacy and...
Seyed Mohammad Hadi Hosseini, Amir Najafi, Mahdieh Soleymani Baghshah
Bandit algorithms have recently emerged as a powerful tool for evaluating machine learning models, including generative image models and large...
Haobo Wang, Weiqi Luo, Xiaojun Jia +1 more
Large vision-language models (VLMs) are vulnerable to transfer-based adversarial perturbations, enabling attackers to optimize on surrogate models...
Xiaoyu Wen, Zhida He, Han Qi +7 more
Ensuring robust safety alignment is crucial for Large Language Models (LLMs), yet existing defenses often lag behind evolving adversarial attacks due...
Poushali Sengupta, Shashi Raj Pandey, Sabita Maharjan +1 more
Large language models (LLMs) generate outputs by utilizing extensive context, which often includes redundant information from prompts, retrieved...
Eliron Rahimi, Elad Hirshel, Rom Himelstein +3 more
Diffusion language models (DLMs) have recently emerged as a promising alternative to autoregressive (AR) models, offering parallel decoding and...
Ziyue Wang, Jiangshan Yu, Kaihua Qin +3 more
Decentralized Finance (DeFi) has turned blockchains into financial infrastructure, allowing anyone to trade, lend, and build protocols without...
Terry Yue Zhuo, Yangruibo Ding, Wenbo Guo +1 more
For over a decade, cybersecurity has relied on human labor scarcity to limit attackers to high-value targets manually or generic automated attacks at...
Xinyi Hou, Shenao Wang, Yifan Zhang +4 more
Agentic AI systems built around large language models (LLMs) are moving away from closed, single-model frameworks and toward open ecosystems that...
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