Cover Image

Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model Stealing

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhao, Yunlong, Deng, Xiaoheng, Liu, Yijing, Pei, Xinjun, Xia, Jiazhi, Chen, Wei
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Examining the Threat Landscape: Foundation Models and Model Stealing
by: Raj, Ankita, et al.
Published: (2025)

Assessing Risk of Stealing Proprietary Models for Medical Imaging Tasks
by: Raj, Ankita, et al.
Published: (2025)

CipherDM: Secure Three-Party Inference for Diffusion Model Sampling
by: Zhao, Xin, et al.
Published: (2024)

Making Every Step Effective: Jailbreaking Large Vision-Language Models Through Hierarchical KV Equalization
by: Hao, Shuyang, et al.
Published: (2025)

Lightweight True In-Pixel Encryption with FeFET Enabled Pixel Design for Secure Imaging
by: Udoy, Md Rahatul Islam, et al.
Published: (2026)

Gungnir: Exploiting Stylistic Features in Images for Backdoor Attacks on Diffusion Models
by: Zhang, Lei, et al.
Published: (2025)

Adversarial Sparse Teacher: Defense Against Distillation-Based Model Stealing Attacks Using Adversarial Examples
by: Yilmaz, Eda, et al.
Published: (2024)

Versatile Backdoor Attack with Visible, Semantic, Sample-Specific, and Compatible Triggers
by: Wang, Ruotong, et al.
Published: (2023)

Exploit the Leak: Understanding Risks in Biometric Matchers
by: Durbet, Axel, et al.
Published: (2023)

Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios
by: Li, Ziqiang, et al.
Published: (2023)

Private Gradient Estimation is Useful for Generative Modeling
by: Liu, Bochao, et al.
Published: (2023)

mmSpyVR: Exploiting mmWave Radar for Penetrating Obstacles to Uncover Privacy Vulnerability of Virtual Reality
by: Mei, Luoyu, et al.
Published: (2024)

Exploring Multi-view Pixel Contrast for General and Robust Image Forgery Localization
by: Lou, Zijie, et al.
Published: (2024)

SAME: Sample Reconstruction against Model Extraction Attacks
by: Xie, Yi, et al.
Published: (2023)

Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption
by: Yalavarthi, Bharat, et al.
Published: (2024)

Multimodal Privacy-Preserving Entity Resolution with Fully Homomorphic Encryption
by: Roy, Susim, et al.
Published: (2026)

Is Diffusion Model Safe? Severe Data Leakage via Gradient-Guided Diffusion Model
by: Meng, Jiayang, et al.
Published: (2024)

AMB-FHE: Adaptive Multi-biometric Fusion with Fully Homomorphic Encryption
by: Bayer, Florian, et al.
Published: (2025)

Towards Sample-specific Backdoor Attack with Clean Labels via Attribute Trigger
by: Zhu, Mingyan, et al.
Published: (2023)

UVL2: A Unified Framework for Video Tampering Localization
by: Pei, Pengfei
Published: (2023)

Pixel-Inconsistency Modeling for Image Manipulation Localization
by: Kong, Chenqi, et al.
Published: (2023)

Improving Adversarial Transferability with Neighbourhood Gradient Information
by: Guo, Haijing, et al.
Published: (2024)

Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images
by: Gao, Kuofeng, et al.
Published: (2024)

CIS-BA: Continuous Interaction Space Based Backdoor Attack for Object Detection in the Real-World
by: Zhao, Shuxin, et al.
Published: (2025)

Pura: An Efficient Privacy-Preserving Solution for Face Recognition
by: Xu, Guotao, et al.
Published: (2025)

Adversarial 3D Virtual Patches using Integrated Gradients
by: You, Chengzeng, et al.
Published: (2024)

MedBN: Robust Test-Time Adaptation against Malicious Test Samples
by: Park, Hyejin, et al.
Published: (2024)

Gradient Inversion of Federated Diffusion Models
by: Huang, Jiyue, et al.
Published: (2024)

Gradient-based facial encoding for key generation to encrypt and decrypt multimedia data
by: Patel, Ankit Kumar, et al.
Published: (2024)

A Proxy Attack-Free Strategy for Practically Improving the Poisoning Efficiency in Backdoor Attacks
by: Li, Ziqiang, et al.
Published: (2023)

Improving the Perturbation-Based Explanation of Deepfake Detectors Through the Use of Adversarially-Generated Samples
by: Tsigos, Konstantinos, et al.
Published: (2025)

QuantAttack: Exploiting Dynamic Quantization to Attack Vision Transformers
by: Baras, Amit, et al.
Published: (2023)

FedSECA: Sign Election and Coordinate-wise Aggregation of Gradients for Byzantine Tolerant Federated Learning
by: Benjamin, Joseph Geo, et al.
Published: (2024)

RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance
by: Lin, Miao, et al.
Published: (2026)

TriQDef: Disrupting Semantic and Gradient Alignment to Prevent Adversarial Patch Transferability in Quantized Neural Networks
by: Guesmi, Amira, et al.
Published: (2025)

Err on the Side of Texture: Texture Bias on Real Data
by: Hoak, Blaine, et al.
Published: (2024)

DDIM-Driven Coverless Steganography Scheme with Real Key
by: Yu, Mingyu, et al.
Published: (2024)

SuperPure: Efficient Purification of Localized and Distributed Adversarial Patches via Super-Resolution GAN Models
by: Khalili, Hossein, et al.
Published: (2025)

Frequency Bias Matters: Diving into Robust and Generalized Deep Image Forgery Detection
by: Liu, Chi, et al.
Published: (2025)

Patronus: Safeguarding Text-to-Image Models against White-Box Adversaries
by: Li, Xinfeng, et al.
Published: (2025)