:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Liu, Ruixuan, Wang, Tianhao, Cao, Yang, Xiong, Li
Format:	Preprint
Publié:	2024
Sujets:	Cryptography and Security
Accès en ligne:	https://arxiv.org/abs/2403.09562
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

UniAud: A Unified Auditing Framework for High Auditing Power and Utility with One Training Run
par: Liu, Ruixuan, et autres
Publié: (2025)

ExpShield: Safeguarding Web Text from Unauthorized Crawling and LLM Exploitation
par: Liu, Ruixuan, et autres
Publié: (2024)

Enhancing Pre-Trained Language Models for Vulnerability Detection via Semantic-Preserving Data Augmentation
par: Qi, Weiliang, et autres
Publié: (2024)

Revisiting Privacy-Utility Trade-off for DP Training with Pre-existing Knowledge
par: Zheng, Yu, et autres
Publié: (2024)

SnapAudit: Active Auditing of Differentially Private In-Context Learning via Snapshot-Based Simulation
par: Xia, Yuyang, et autres
Publié: (2025)

Benchmarking Secure Sampling Protocols for Differential Privacy
par: Fu, Yucheng, et autres
Publié: (2024)

Machine Unlearning of Pre-trained Large Language Models
par: Yao, Jin, et autres
Publié: (2024)

How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?
par: Liu, Meiqi, et autres
Publié: (2025)

Direct Token Optimization: A Self-contained Approach to Large Language Model Unlearning
par: Lee, Hong kyu, et autres
Publié: (2025)

Network-Aware Differential Privacy
par: Li, Zhou, et autres
Publié: (2025)

FedSGT: Exact Federated Unlearning via Sequential Group-based Training
par: Zhang, Bokang, et autres
Publié: (2025)

VertMark: A Unified Training-Free Robust Watermarking Framework for Vertical Domain Pre-trained Language Models
par: Kong, Cong, et autres
Publié: (2026)

Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run
par: Xiang, Zihang, et autres
Publié: (2025)

Patronus: Identifying and Mitigating Transferable Backdoors in Pre-trained Language Models
par: Zhao, Tianhang, et autres
Publié: (2025)

Winter Soldier: Backdooring Language Models at Pre-Training with Indirect Data Poisoning
par: Bouaziz, Wassim, et autres
Publié: (2025)

Tight Privacy Audit in One Run
par: Xiang, Zihang, et autres
Publié: (2025)

Language of Network: A Generative Pre-trained Model for Encrypted Traffic Comprehension
par: Zhao, Di, et autres
Publié: (2025)

Enhanced Privacy Bound for Shuffle Model with Personalized Privacy
par: Liu, Yixuan, et autres
Publié: (2024)

APT-CGLP: Advanced Persistent Threat Hunting via Contrastive Graph-Language Pre-Training
par: Qiu, Xuebo, et autres
Publié: (2025)

The Security and Privacy of Mobile Edge Computing: An Artificial Intelligence Perspective
par: Wang, Cheng, et autres
Publié: (2024)

Persistent Pre-Training Poisoning of LLMs
par: Zhang, Yiming, et autres
Publié: (2024)

Detecting Malicious Intents in Smart Contracts with Pre-trained Programming Language Models
par: Huang, Youwei, et autres
Publié: (2025)

Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models
par: Wen, Yuxin, et autres
Publié: (2024)

PrePaMS: Privacy-Preserving Participant Management System for Studies with Rewards and Prerequisites
par: Meißner, Echo, et autres
Publié: (2024)

Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls
par: Sánchez, Pedro Miguel Sánchez, et autres
Publié: (2024)

PrivCode: When Code Generation Meets Differential Privacy
par: Liu, Zheng, et autres
Publié: (2025)

Preserving Node-level Privacy in Graph Neural Networks
par: Xiang, Zihang, et autres
Publié: (2023)

Always be Pre-Training: Representation Learning for Network Intrusion Detection with GNNs
par: Gu, Zhengyao, et autres
Publié: (2024)

UOR: Universal Backdoor Attacks on Pre-trained Language Models
par: Du, Wei, et autres
Publié: (2023)

Provable Privacy with Non-Private Pre-Processing
par: Hu, Yaxi, et autres
Publié: (2024)

Private Means and the Curious Incident of the Free Lunch
par: Fitzsimons, Jack, et autres
Publié: (2024)

Beyond Indistinguishability: Measuring Extraction Risk in LLM APIs
par: Liu, Ruixuan, et autres
Publié: (2026)

Delayed Backdoor Attacks: Exploring the Temporal Dimension as a New Attack Surface in Pre-Trained Models
par: Ding, Zikang, et autres
Publié: (2026)

Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models
par: He, Yu, et autres
Publié: (2025)

Augmenting Parameter-Efficient Pre-trained Language Models with Large Language Models
par: Anand, Saurabh, et autres
Publié: (2026)

FedRE: Robust and Effective Federated Learning with Privacy Preference
par: Xiao, Tianzhe, et autres
Publié: (2025)

MIA-Tuner: Adapting Large Language Models as Pre-training Text Detector
par: Fu, Wenjie, et autres
Publié: (2024)

Protecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking
par: Kong, Cong, et autres
Publié: (2024)

Black-box Membership Inference Attacks against Fine-tuned Diffusion Models
par: Pang, Yan, et autres
Publié: (2023)

Revisiting Pre-trained Language Models for Vulnerability Detection
par: Li, Youpeng, et autres
Publié: (2025)