Copertina

Adversarial Example Based Fingerprinting for Robust Copyright Protection in Split Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Lin, Zhangting, Xue, Mingfu, Chen, Kewei, Liu, Wenmao, Gao, Xiang, Zhang, Leo Yu, Wang, Jian, Zhang, Yushu
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Cryptography and Security
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Imperceptible Sample-Specific Backdoor to DNN with Denoising Autoencoder
di: Wang, Xiangqi, et al.
Pubblicazione: (2023)

FairCMS: Cloud Media Sharing with Fair Copyright Protection
di: Xiao, Xiangli, et al.
Pubblicazione: (2021)

Protecting Deep Learning Model Copyrights with Adversarial Example-Free Reuse Detection
di: Luan, Xiaokun, et al.
Pubblicazione: (2024)

IrisFP: Adversarial-Example-based Model Fingerprinting with Enhanced Uniqueness and Robustness
di: Geng, Ziye, et al.
Pubblicazione: (2026)

Masked Language Model Based Textual Adversarial Example Detection
di: Zhang, Xiaomei, et al.
Pubblicazione: (2023)

Lossless Copyright Protection via Intrinsic Model Fingerprinting
di: Chen, Lingxiao, et al.
Pubblicazione: (2026)

DataCook: Crafting Anti-Adversarial Examples for Healthcare Data Copyright Protection
di: Shang, Sihan, et al.
Pubblicazione: (2024)

Make Identity Unextractable yet Perceptible: Synthesis-Based Privacy Protection for Subject Faces in Photos
di: Wang, Tao, et al.
Pubblicazione: (2025)

ALRPHFS: Adversarially Learned Risk Patterns with Hierarchical Fast \& Slow Reasoning for Robust Agent Defense
di: Xiang, Shiyu, et al.
Pubblicazione: (2025)

DataSafe: Copyright Protection with PUF Watermarking and Blockchain Tracking
di: Xue, Xiaolong, et al.
Pubblicazione: (2024)

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends
di: Xu, Zhenhua, et al.
Pubblicazione: (2025)

From Compression to Accountability: Harmless Copyright Protection for Dataset Distillation
di: Liang, Yan, et al.
Pubblicazione: (2026)

WATER-GS: Toward Copyright Protection for 3D Gaussian Splatting via Universal Watermarking
di: Tan, Yuqi, et al.
Pubblicazione: (2024)

Robustness Over Time: Understanding Adversarial Examples' Effectiveness on Longitudinal Versions of Large Language Models
di: Liu, Yugeng, et al.
Pubblicazione: (2023)

Constraint-based Adversarial Example Synthesis
di: Yu, Fang, et al.
Pubblicazione: (2024)

Adversarial Attacks Against Deep Learning-Based Radio Frequency Fingerprint Identification
di: Ma, Jie, et al.
Pubblicazione: (2025)

Are Robust LLM Fingerprints Adversarially Robust?
di: Nasery, Anshul, et al.
Pubblicazione: (2025)

AGATE: Stealthy Black-box Watermarking for Multimodal Model Copyright Protection
di: Gao, Jianbo, et al.
Pubblicazione: (2025)

Image Privacy Protection: A Survey
di: Wen, Wenying, et al.
Pubblicazione: (2024)

DWBench: Holistic Evaluation of Watermark for Dataset Copyright Auditing
di: Ren, Xiao, et al.
Pubblicazione: (2026)

Robust AI-Synthesized Speech Detection Using Feature Decomposition Learning and Synthesizer Feature Augmentation
di: Zhang, Kuiyuan, et al.
Pubblicazione: (2024)

NeuroTrace: Inference Provenance-Based Detection of Adversarial Examples
di: Hmida, Firas Ben, et al.
Pubblicazione: (2026)

NCCR: to Evaluate the Robustness of Neural Networks and Adversarial Examples
di: Pu, Shi, et al.
Pubblicazione: (2025)

Marlin: Knowledge-Driven Analysis of Provenance Graphs for Efficient and Robust Detection of Cyber Attacks
di: Li, Zhenyuan, et al.
Pubblicazione: (2024)

Position: Towards Resilience Against Adversarial Examples
di: Dai, Sihui, et al.
Pubblicazione: (2024)

Laundering AI Authority with Adversarial Examples
di: Zhang, Jie, et al.
Pubblicazione: (2026)

An Adversarial Robust Behavior Sequence Anomaly Detection Approach Based on Critical Behavior Unit Learning
di: Zhan, Dongyang, et al.
Pubblicazione: (2025)

To See or Not to See -- Fingerprinting Devices in Adversarial Environments Amid Advanced Machine Learning
di: Feng, Justin, et al.
Pubblicazione: (2025)

Obfuscating IoT Device Scanning Activity via Adversarial Example Generation
di: Li, Haocong, et al.
Pubblicazione: (2024)

Towards Privacy-Preserving Split Learning: Destabilizing Adversarial Inference and Reconstruction Attacks in the Cloud
di: Higgins, Griffin, et al.
Pubblicazione: (2025)

Prediction Inconsistency Helps Achieve Generalizable Detection of Adversarial Examples
di: Han, Sicong, et al.
Pubblicazione: (2025)

DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection
di: Liu, Jiang, et al.
Pubblicazione: (2023)

Double-I Watermark: Protecting Model Copyright for LLM Fine-tuning
di: Li, Shen, et al.
Pubblicazione: (2024)

Constructing Semantics-Aware Adversarial Examples with a Probabilistic Perspective
di: Zhang, Andi, et al.
Pubblicazione: (2023)

Rotation, Scale, and Translation Resilient Black-box Fingerprinting for Intellectual Property Protection of EaaS Models
di: Zhang, Hongjie, et al.
Pubblicazione: (2025)

HidePrint: Protecting Device Anonymity by Obscuring Radio Fingerprints
di: Oligeri, Gabriele, et al.
Pubblicazione: (2024)

Towards Channel-Robust and Receiver-Independent Radio Frequency Fingerprint Identification
di: Ma, Jie, et al.
Pubblicazione: (2025)

Deep Learning-based Dual Watermarking for Image Copyright Protection and Authentication
di: Padhi, Sudev Kumar, et al.
Pubblicazione: (2025)

Detecting Adversarial Examples
di: Mumcu, Furkan, et al.
Pubblicazione: (2024)

Not All Edges are Equally Robust: Evaluating the Robustness of Ranking-Based Federated Learning
di: Gong, Zirui, et al.
Pubblicazione: (2025)