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How to Steer Your Adversary: Targeted and Efficient Model Stealing
  Defenses with Gradient Redirection

How to Steer Your Adversary: Targeted and Efficient Model Stealing Defenses with Gradient Redirection

28 June 2022
Mantas Mazeika
Yangqiu Song
David A. Forsyth
    AAML
ArXiv (abs)PDFHTML

Papers citing "How to Steer Your Adversary: Targeted and Efficient Model Stealing Defenses with Gradient Redirection"

14 / 14 papers shown
Title
Attackers Can Do Better: Over- and Understated Factors of Model Stealing Attacks
Daryna Oliynyk
Rudolf Mayer
Andreas Rauber
AAML
86
0
0
08 Mar 2025
Decoder Gradient Shield: Provable and High-Fidelity Prevention of Gradient-Based Box-Free Watermark Removal
Decoder Gradient Shield: Provable and High-Fidelity Prevention of Gradient-Based Box-Free Watermark Removal
Haonan An
Guang Hua
Zhengru Fang
Guowen Xu
Susanto Rahardja
Yuguang Fang
AAML
139
0
0
28 Feb 2025
Examining the Threat Landscape: Foundation Models and Model Stealing
Examining the Threat Landscape: Foundation Models and Model Stealing
Ankita Raj
Deepankar Varma
Chetan Arora
AAML
293
1
0
25 Feb 2025
Neural Honeytrace: A Robust Plug-and-Play Watermarking Framework against Model Extraction Attacks
Neural Honeytrace: A Robust Plug-and-Play Watermarking Framework against Model Extraction Attacks
Yixiao Xu
Binxing Fang
Rui Wang
Yinghai Zhou
S. Ji
Yuan Liu
Mohan Li
AAMLMIACV
150
0
0
16 Jan 2025
Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model
  Stealing
Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model Stealing
Yunlong Zhao
Xiaoheng Deng
Yijing Liu
Xin-jun Pei
Jiazhi Xia
Wei Chen
AAML
48
3
0
18 May 2024
A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed
  Identity of DNN Model
A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed Identity of DNN Model
Tianxiu Xie
Keke Gai
Jing Yu
Liehuang Zhu
Kim-Kwang Raymond Choo
75
0
0
07 May 2024
Binary Linear Tree Commitment-based Ownership Protection for Distributed
  Machine Learning
Binary Linear Tree Commitment-based Ownership Protection for Distributed Machine Learning
Tianxiu Xie
Keke Gai
Jing Yu
Liehuang Zhu
FedML
43
0
0
11 Jan 2024
Efficient Defense Against Model Stealing Attacks on Convolutional Neural
  Networks
Efficient Defense Against Model Stealing Attacks on Convolutional Neural Networks
Kacem Khaled
Mouna Dhaouadi
F. Magalhães
Gabriela Nicolescu
AAML
32
2
0
04 Sep 2023
Isolation and Induction: Training Robust Deep Neural Networks against
  Model Stealing Attacks
Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks
Jun Guo
Aishan Liu
Xingyu Zheng
Siyuan Liang
Yisong Xiao
Yichao Wu
Xianglong Liu
AAML
86
13
0
02 Aug 2023
FDINet: Protecting against DNN Model Extraction via Feature Distortion
  Index
FDINet: Protecting against DNN Model Extraction via Feature Distortion Index
Hongwei Yao
Zheng Li
Haiqin Weng
Feng Xue
Kui Ren
Zhan Qin
92
4
0
20 Jun 2023
ModelObfuscator: Obfuscating Model Information to Protect Deployed
  ML-based Systems
ModelObfuscator: Obfuscating Model Information to Protect Deployed ML-based Systems
Mingyi Zhou
Xiang Gao
Jing Wu
John C. Grundy
Xiao Chen
Chunyang Chen
Li Li
AAML
109
13
0
01 Jun 2023
On the Robustness of Dataset Inference
On the Robustness of Dataset Inference
S. Szyller
Rui Zhang
Enchao Gong
Nadarajah Asokan
AAML
62
6
0
24 Oct 2022
I Know What You Trained Last Summer: A Survey on Stealing Machine
  Learning Models and Defences
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences
Daryna Oliynyk
Rudolf Mayer
Andreas Rauber
116
114
0
16 Jun 2022
Thieves on Sesame Street! Model Extraction of BERT-based APIs
Thieves on Sesame Street! Model Extraction of BERT-based APIs
Kalpesh Krishna
Gaurav Singh Tomar
Ankur P. Parikh
Nicolas Papernot
Mohit Iyyer
MIACVMLAU
156
201
0
27 Oct 2019
1