:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Li, Qi, Wang, Cheng-Long, Cao, Yinzhi, Wang, Di
Format:	Preprint
Publié:	2024
Sujets:	Cryptography and Security Artificial Intelligence
Accès en ligne:	https://arxiv.org/abs/2411.15796
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness
par: Wang, Cheng-Long, et autres
Publié: (2025)

CoLA: A Choice Leakage Attack Framework to Expose Privacy Risks in Subset Training
par: Li, Qi, et autres
Publié: (2026)

Uncovering Logit Suppression Vulnerabilities in LLM Safety Alignment
par: Li, Yuxi, et autres
Publié: (2024)

When Grammar Guides the Attack: Uncovering Control-Plane Vulnerabilities in LLMs with Structured Output
par: Zhang, Shuoming, et autres
Publié: (2025)

Data Quality Issues in Vulnerability Detection Datasets
par: Guo, Yuejun, et autres
Publié: (2024)

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

MemLineage: Lineage-Guided Enforcement for LLM Agent Memory
par: Ouyang, Ciyan, et autres
Publié: (2026)

PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration
par: Zeng, Ziqian, et autres
Publié: (2024)

Detecting Privilege Escalation in Polyglot Microservices via Agentic Program Analysis
par: Li, Penghui, et autres
Publié: (2026)

Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Approximate Unlearning Completeness
par: Wang, Cheng-Long, et autres
Publié: (2024)

Towards Confidential and Efficient LLM Inference with Dual Privacy Protection
par: Yu, Honglan, et autres
Publié: (2025)

A Practical Framework for Evaluating Medical AI Security: Reproducible Assessment of Jailbreaking and Privacy Vulnerabilities Across Clinical Specialties
par: Wang, Jinghao, et autres
Publié: (2025)

PLeak: Prompt Leaking Attacks against Large Language Model Applications
par: Hui, Bo, et autres
Publié: (2024)

Mirror Mirror on the Wall, Have I Forgotten it All? A New Framework for Evaluating Machine Unlearning
par: Brimhall, Brennon, et autres
Publié: (2025)

Comment and Control: Hijacking Agentic Workflows via Context-Grounded Evolution
par: Fendley, Neil, et autres
Publié: (2026)

Amplified Vulnerabilities: Structured Jailbreak Attacks on LLM-based Multi-Agent Debate
par: Qi, Senmao, et autres
Publié: (2025)

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

LLM-PBE: Assessing Data Privacy in Large Language Models
par: Li, Qinbin, et autres
Publié: (2024)

AI-Based Vulnerability Analysis of NFT Smart Contracts
par: Wang, Xin, et autres
Publié: (2025)

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

VerilogLAVD: LLM-Aided Rule Generation for Vulnerability Detection in Verilog
par: Long, Xiang, et autres
Publié: (2025)

Dual-Priv Pruning : Efficient Differential Private Fine-Tuning in Multimodal Large Language Models
par: Wei, Qianshan, et autres
Publié: (2025)

Your Privacy Depends on Others: Collusion Vulnerabilities in Individual Differential Privacy
par: Kaiser, Johannes, et autres
Publié: (2026)

PRSI: Privacy-Preserving Recommendation Model Based on Vector Splitting and Interactive Protocols
par: Cao, Xiaokai, et autres
Publié: (2024)

No Free Lunch Theorem for Privacy-Preserving LLM Inference
par: Zhang, Xiaojin, et autres
Publié: (2024)

Taught by the Flawed: How Dataset Insecurity Breeds Vulnerable AI Code
par: Xia, Catherine, et autres
Publié: (2025)

CHAI: Command Hijacking against embodied AI
par: Burbano, Luis, et autres
Publié: (2025)

User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Data
par: Yang, Haowei, et autres
Publié: (2025)

State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey
par: Zhang, Chaoyu, et autres
Publié: (2024)

SoK: Semantic Privacy in Large Language Models
par: Ma, Baihe, et autres
Publié: (2025)

VULPO: Context-Aware Vulnerability Detection via On-Policy LLM Optimization
par: Li, Youpeng, et autres
Publié: (2025)

Context Lineage Assurance for Non-Human Identities in Critical Multi-Agent Systems
par: Malkapuram, Sumana, et autres
Publié: (2025)

Analyzing Inference Privacy Risks Through Gradients in Machine Learning
par: Li, Zhuohang, et autres
Publié: (2024)

Connect the dots: Dataset Condensation, Differential Privacy, and Adversarial Uncertainty
par: Odoh, Kenneth
Publié: (2024)

Cross-Cloud Data Privacy Protection: Optimizing Collaborative Mechanisms of AI Systems by Integrating Federated Learning and LLMs
par: Luo, Huaiying, et autres
Publié: (2025)

Differential Privacy in Federated Learning: Mitigating Inference Attacks with Randomized Response
par: Ozturk, Ozer, et autres
Publié: (2025)

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

Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage
par: Wang, Qin, et autres
Publié: (2024)

Compiled Models, Built-In Exploits: Uncovering Pervasive Bit-Flip Attack Surfaces in DNN Executables
par: Chen, Yanzuo, et autres
Publié: (2023)

Zero-Knowledge Federated Learning: A New Trustworthy and Privacy-Preserving Distributed Learning Paradigm
par: Wang, Taotao, et autres
Publié: (2025)