Imagen de Portada

FDINet: Protecting against DNN Model Extraction via Feature Distortion Index

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Yao, Hongwei, Li, Zheng, Weng, Haiqin, Xue, Feng, Qin, Zhan, Ren, Kui
Formato:	Preprint
Publicado:	2023
Materias:	Cryptography and Security Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution
por: Shao, Shuo, et al.
Publicado: (2024)

FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis
por: He, Yiling, et al.
Publicado: (2023)

ProDiF: Protecting Domain-Invariant Features to Secure Pre-Trained Models Against Extraction
por: Zhou, Tong, et al.
Publicado: (2025)

Eguard: Defending LLM Embeddings Against Inversion Attacks via Text Mutual Information Optimization
por: Liu, Tiantian, et al.
Publicado: (2024)

FIT-Print: Towards False-claim-resistant Model Ownership Verification via Targeted Fingerprint
por: Shao, Shuo, et al.
Publicado: (2025)

ControlNET: A Firewall for RAG-based LLM System
por: Yao, Hongwei, et al.
Publicado: (2025)

Adaptive Backtracking for Privacy Protection in Large Language Models
por: Yao, Zhihao, et al.
Publicado: (2025)

Channel-Level Semantic Perturbations: Unlearnable Examples for Diverse Training Paradigms
por: Wang, Bo, et al.
Publicado: (2026)

External Data Extraction Attacks against Retrieval-Augmented Large Language Models
por: He, Yu, et al.
Publicado: (2025)

MEA-Defender: A Robust Watermark against Model Extraction Attack
por: Lv, Peizhuo, et al.
Publicado: (2024)

Model Extraction Attacks Revisited
por: Liang, Jiacheng, et al.
Publicado: (2023)

MAJIC: Markovian Adaptive Jailbreaking via Iterative Composition of Diverse Innovative Strategies
por: Qi, Weiwei, et al.
Publicado: (2025)

FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model
por: Shao, Shuo, et al.
Publicado: (2022)

AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models
por: Oksuz, Abdullah Caglar, et al.
Publicado: (2023)

RobPI: Robust Private Inference against Malicious Client
por: Xue, Jiaqi, et al.
Publicado: (2026)

Privacy-Preserving Inference for Quantized BERT Models
por: Lu, Tianpei, et al.
Publicado: (2025)

Towards Identification and Intervention of Safety-Critical Parameters in Large Language Models
por: Qi, Weiwei, et al.
Publicado: (2026)

BadReward: Clean-Label Poisoning of Reward Models in Text-to-Image RLHF
por: Duan, Kaiwen, et al.
Publicado: (2025)

Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy
por: Aliakbarpour, Maryam, et al.
Publicado: (2024)

TBNet: A Neural Architectural Defense Framework Facilitating DNN Model Protection in Trusted Execution Environments
por: Liu, Ziyu, et al.
Publicado: (2024)

Model-Guardian: Protecting against Data-Free Model Stealing Using Gradient Representations and Deceptive Predictions
por: Yang, Yunfei, et al.
Publicado: (2025)

DivQAT: Enhancing Robustness of Quantized Convolutional Neural Networks against Model Extraction Attacks
por: Khaled, Kacem, et al.
Publicado: (2025)

MACPruning: Dynamic Operation Pruning to Mitigate Side-Channel DNN Model Extraction
por: Ding, Ruyi, et al.
Publicado: (2025)

Efficient Model Extraction via Boundary Sampling
por: Dor, Maor Biton, et al.
Publicado: (2024)

Runtime Stealthy Perception Attacks against DNN-based Adaptive Cruise Control Systems
por: Zhou, Xugui, et al.
Publicado: (2023)

Differentially Private Random Feature Model
por: Liao, Chunyang, et al.
Publicado: (2024)

Defense against Poisoning Attacks under Shuffle-DP
por: Wang, Siyi, et al.
Publicado: (2026)

Breaking Distortion-free Watermarks in Large Language Models
por: Reynolds, Shayleen, et al.
Publicado: (2025)

AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing
por: Zhou, Tong, et al.
Publicado: (2024)

ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
por: Cheng, Zhan, et al.
Publicado: (2025)

Distortion-free Watermarks are not Truly Distortion-free under Watermark Key Collisions
por: Wu, Yihan, et al.
Publicado: (2024)

Strong Copyright Protection for Language Models via Adaptive Model Fusion
por: Abad, Javier, et al.
Publicado: (2024)

Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models
por: He, Yu, et al.
Publicado: (2025)

PDFInspect: A Unified Feature Extraction Framework for Malicious Document Detection
por: P, Sharmila S
Publicado: (2026)

A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective
por: Yu, Lei, et al.
Publicado: (2024)

ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach
por: Hu, Yuke, et al.
Publicado: (2023)

Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks
por: Xue, Lulu, et al.
Publicado: (2024)

AttriGuard: Defeating Indirect Prompt Injection in LLM Agents via Causal Attribution of Tool Invocations
por: He, Yu, et al.
Publicado: (2026)

Few-shot Model Extraction Attacks against Sequential Recommender Systems
por: Zhang, Hui, et al.
Publicado: (2024)

The Communication-Friendly Privacy-Preserving Machine Learning against Malicious Adversaries
por: Lu, Tianpei, et al.
Publicado: (2024)