2,529+ academic papers on AI security, attacks, and defenses
Showing 281–300 of 312 papers
Clear filtersTiancheng Xing, Jerry Li, Yixuan Du +1 more
Large language models (LLMs) are increasingly used as rerankers in information retrieval, yet their ranking behavior can be steered by small,...
Zizhao Wang, Dingcheng Li, Vaishakh Keshava +4 more
Large Language Model (LLM) agents can leverage tools such as Google Search to complete complex tasks. However, this tool usage introduces the risk of...
Guangyu Shen, Siyuan Cheng, Xiangzhe Xu +4 more
Large Language Models (LLMs) can acquire deceptive behaviors through backdoor attacks, where the model executes prohibited actions whenever secret...
Tanqiu Jiang, Min Bai, Nikolaos Pappas +2 more
Vision-language model (VLM)-based web agents increasingly power high-stakes selection tasks like content recommendation or product ranking by...
Fatmazohra Rezkellah, Ramzi Dakhmouche
With the increasing adoption of Large Language Models (LLMs), more customization is needed to ensure privacy-preserving and safe generation. We...
Abrar Shahid, Ibteeker Mahir Ishum, AKM Tahmidul Haque +2 more
This paper presents a controlled study of adversarial reinforcement learning in network security through a custom OpenAI Gym environment that models...
Davide Gabrielli, Simone Sestito, Iacopo Masi
The current landscape of defensive mechanisms for LLMs is fragmented and underdeveloped, unlike prior work on classifiers. To further promote...
Youwei Bao, Shuhan Yang, Hyunsoo Yang
Deterministic pseudo random number generators (PRNGs) used in generative artificial intelligence (GAI) models produce predictable patterns vulnerable...
Zhenyu Pan, Yiting Zhang, Zhuo Liu +13 more
LLM-based multi-agent systems excel at planning, tool use, and role coordination, but their openness and interaction complexity also expose them to...
Jaiden Fairoze, Sanjam Garg, Keewoo Lee +1 more
As large language models (LLMs) advance, ensuring AI safety and alignment is paramount. One popular approach is prompt guards, lightweight mechanisms...
Yen-Shan Chen, Sian-Yao Huang, Cheng-Lin Yang +1 more
Existing data poisoning attacks on retrieval-augmented generation (RAG) systems scale poorly because they require costly optimization of poisoned...
Tsubasa Takahashi, Shojiro Yamabe, Futa Waseda +1 more
Differential Attention (DA) has been proposed as a refinement to standard attention, suppressing redundant or noisy context through a subtractive...
Yu Yan, Siqi Lu, Yang Gao +4 more
Recently, Bit-Flip Attack (BFA) has garnered widespread attention for its ability to compromise software system integrity remotely through hardware...
Dalal 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...
Get breaking CVE alerts, compliance reports (ISO 42001, EU AI Act), and CISO risk assessments for your AI/ML stack.
Start 14-Day Free Trial
AI Threat Alert