Image de couverture de livre

AED: Automatic Discovery of Effective and Diverse Vulnerabilities for Autonomous Driving Policy with Large Language Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Qiu, Le, Xu, Zelai, Tan, Qixin, Tang, Wenhao, Yu, Chao, Wang, Yu
Format:	Preprint
Publié:	2025
Sujets:	Cryptography and Security Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Study of Vulnerability Repair in JavaScript Programs with Large Language Models
par: Le, Tan Khang, et autres
Publié: (2024)

Retrieval Augmented Generation Integrated Large Language Models in Smart Contract Vulnerability Detection
par: Yu, Jeffy
Publié: (2024)

PrompTrend: Continuous Community-Driven Vulnerability Discovery and Assessment for Large Language Models
par: Gasmi, Tarek, et autres
Publié: (2025)

MCPGuard : Automatically Detecting Vulnerabilities in MCP Servers
par: Wang, Bin, et autres
Publié: (2025)

Breaking the Loop: Detecting and Mitigating Denial-of-Service Vulnerabilities in Large Language Models
par: Yu, Junzhe, et autres
Publié: (2025)

Evaluating Adversarial Vulnerabilities in Modern Large Language Models
par: Perel, Tom
Publié: (2025)

Exploiting the Vulnerability of Large Language Models via Defense-Aware Architectural Backdoor
par: Miah, Abdullah Arafat, et autres
Publié: (2024)

Asymmetry Vulnerability and Physical Attacks on Online Map Construction for Autonomous Driving
par: Lou, Yang, et autres
Publié: (2025)

Exploring Membership Inference Vulnerabilities in Clinical Large Language Models
par: Nemecek, Alexander, et autres
Publié: (2025)

VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models
par: Liu, Yu, et autres
Publié: (2024)

MEraser: An Effective Fingerprint Erasure Approach for Large Language Models
par: Zhang, Jingxuan, et autres
Publié: (2025)

Unvalidated Trust: Cross-Stage Vulnerabilities in Large Language Model Architectures
par: Schwarz, Dominik
Publié: (2025)

An Engorgio Prompt Makes Large Language Model Babble on
par: Dong, Jianshuo, et autres
Publié: (2024)

Conflicts Make Large Reasoning Models Vulnerable to Attacks
par: Liu, Honghao, et autres
Publié: (2026)

MARVEL: Multi-Agent RTL Vulnerability Extraction using Large Language Models
par: Collini, Luca, et autres
Publié: (2025)

Beyond Single Bugs: Benchmarking Large Language Models for Multi-Vulnerability Detection
par: Pushkar, Chinmay, et autres
Publié: (2025)

An Investigation of Large Language Models and Their Vulnerabilities in Spam Detection
par: Tang, Qiyao, et autres
Publié: (2025)

AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks
par: Xu, Jiacen, et autres
Publié: (2024)

Automatically Generating Rules of Malicious Software Packages via Large Language Model
par: Zhang, XiangRui, et autres
Publié: (2025)

CryptoScope: Utilizing Large Language Models for Automated Cryptographic Logic Vulnerability Detection
par: Li, Zhihao, et autres
Publié: (2025)

Code Vulnerability Repair with Large Language Model using Context-Aware Prompt Tuning
par: Khan, Arshiya, et autres
Publié: (2024)

Can Transformer Memory Be Corrupted? Investigating Cache-Side Vulnerabilities in Large Language Models
par: Hossain, Elias, et autres
Publié: (2025)

Transient Turn Injection: Exposing Stateless Multi-Turn Vulnerabilities in Large Language Models
par: Rayhan, Naheed, et autres
Publié: (2026)

Beyond Content Safety: Real-Time Monitoring for Reasoning Vulnerabilities in Large Language Models
par: Wang, Xunguang, et autres
Publié: (2026)

Jailbreaking and Mitigation of Vulnerabilities in Large Language Models
par: Peng, Benji, et autres
Publié: (2024)

Finetuning Large Language Models for Vulnerability Detection
par: Shestov, Alexey, et autres
Publié: (2024)

xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models
par: Luong, Phung Duc, et autres
Publié: (2025)

Large Language Model Watermark Stealing With Mixed Integer Programming
par: Zhang, Zhaoxi, et autres
Publié: (2024)

Federated Large Language Models: Feasibility, Robustness, Security and Future Directions
par: Jiang, Wenhao, et autres
Publié: (2025)

Enhancing Reverse Engineering: Investigating and Benchmarking Large Language Models for Vulnerability Analysis in Decompiled Binaries
par: Manuel, Dylan, et autres
Publié: (2024)

Exploring the Secondary Risks of Large Language Models
par: Chen, Jiawei, et autres
Publié: (2025)

LLbezpeky: Leveraging Large Language Models for Vulnerability Detection
par: Mathews, Noble Saji, et autres
Publié: (2024)

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence
par: Meng, Yuqiao, et autres
Publié: (2025)

AutoPentest: Enhancing Vulnerability Management With Autonomous LLM Agents
par: Henke, Julius
Publié: (2025)

LLM Agents can Autonomously Exploit One-day Vulnerabilities
par: Fang, Richard, et autres
Publié: (2024)

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection
par: Yu, Lei, et autres
Publié: (2025)

Towards Effective Complementary Security Analysis using Large Language Models
par: Wagner, Jonas, et autres
Publié: (2025)

Lost in Modality: Evaluating the Effectiveness of Text-Based Membership Inference Attacks on Large Multimodal Models
par: Tong, Ziyi, et autres
Publié: (2025)

Distilling Lightweight Language Models for C/C++ Vulnerabilities
par: Wei, Zhiyuan, et autres
Publié: (2025)

Watermarking Techniques for Large Language Models: A Survey
par: Liang, Yuqing, et autres
Publié: (2024)