Knockoff Nets: Stealing Functionality of Black-Box Models

6 December 2018

Tribhuvanesh Orekondy

Bernt Schiele

Mario Fritz

MLAU

ArXiv PDF HTML

Papers citing "Knockoff Nets: Stealing Functionality of Black-Box Models"

50 / 104 papers shown

Title
Attackers Can Do Better: Over- and Understated Factors of Model Stealing Attacks Daryna Oliynyk Rudolf Mayer Andreas Rauber AAML 49 0 0 08 Mar 2025
Examining the Threat Landscape: Foundation Models and Model Stealing Ankita Raj Deepankar Varma Chetan Arora AAML 78 1 0 25 Feb 2025
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 Zhihong Tian MIACV AAML 65 0 0 20 Jan 2025
Neural Interactive Proofs Lewis Hammond Sam Adam-Day AAML 89 2 0 12 Dec 2024
A Cost-Aware Approach to Adversarial Robustness in Neural Networks Charles Meyers Mohammad Reza Saleh Sedghpour Tommy Löfstedt Erik Elmroth OOD AAML 33 0 0 11 Sep 2024
On the Weaknesses of Backdoor-based Model Watermarking: An Information-theoretic Perspective Aoting Hu Yanzhi Chen Renjie Xie Adrian Weller 38 0 0 10 Sep 2024
ModelLock: Locking Your Model With a Spell Yifeng Gao Yuhua Sun Xingjun Ma Zuxuan Wu Yu-Gang Jiang VLM 50 1 0 25 May 2024
A Generative Approach to Surrogate-based Black-box Attacks Raha Moraffah Huan Liu AAML 27 0 0 05 Feb 2024
Stolen Subwords: Importance of Vocabularies for Machine Translation Model Stealing Vilém Zouhar AAML 40 0 0 29 Jan 2024
Model Stealing Attack against Recommender System Zhihao Zhu Rui Fan Chenwang Wu Yi Yang Defu Lian Enhong Chen AAML 27 2 0 18 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 47 2 0 07 Dec 2023
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems Guangjing Wang Ce Zhou Yuanda Wang Bocheng Chen Hanqing Guo Qiben Yan AAML SILM 68 3 0 20 Nov 2023
Army of Thieves: Enhancing Black-Box Model Extraction via Ensemble based sample selection Akshit Jindal Vikram Goyal Saket Anand Chetan Arora FedML 20 2 0 08 Nov 2023
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models Boyang Zhang Zheng Li Ziqing Yang Xinlei He Michael Backes Mario Fritz Yang Zhang 33 4 0 19 Oct 2023
SCME: A Self-Contrastive Method for Data-free and Query-Limited Model Extraction Attack Renyang Liu Jinhong Zhang Kwok-Yan Lam Jun Zhao Wei Zhou 25 1 0 15 Oct 2023
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders Jan Dubiñski Stanislaw Pawlak Franziska Boenisch Tomasz Trzciñski Adam Dziedzic AAML 29 3 0 12 Oct 2023
StegGuard: Fingerprinting Self-supervised Pre-trained Encoders via Secrets Embeder and Extractor Xingdong Ren Tianxing Zhang Hanzhou Wu Xinpeng Zhang Yinggui Wang Guangling Sun LLMSV 27 0 0 05 Oct 2023
Towards Few-Call Model Stealing via Active Self-Paced Knowledge Distillation and Diffusion-Based Image Generation Vlad Hondru Radu Tudor Ionescu DiffM 50 1 0 29 Sep 2023
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 38 12 0 02 Aug 2023
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems Debopam Sanyal Jui-Tse Hung Manavi Agrawal Prahlad Jasti Shahab Nikkhoo S. Jha Tianhao Wang Sibin Mohan Alexey Tumanov 51 0 0 03 Jul 2023
The False Promise of Imitating Proprietary LLMs Arnav Gudibande Eric Wallace Charles Burton Snell Xinyang Geng Hao Liu Pieter Abbeel Sergey Levine Dawn Song ALM 44 198 0 25 May 2023
Lion: Adversarial Distillation of Proprietary Large Language Models Yuxin Jiang Chunkit Chan Mingyang Chen Wei Wang ALM 28 23 0 22 May 2023
Finding Meaningful Distributions of ML Black-boxes under Forensic Investigation Jiyi Zhang Hansheng Fang Hwee Kuan Lee E. Chang 18 1 0 10 May 2023
On the Limitations of Model Stealing with Uncertainty Quantification Models David Pape Sina Daubener Thorsten Eisenhofer Antonio Emanuele Cinà Lea Schonherr 36 3 0 09 May 2023
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings Asim Waheed Vasisht Duddu Nadarajah Asokan 35 9 0 17 Apr 2023
On the Adversarial Inversion of Deep Biometric Representations Gioacchino Tangari Shreesh Keskar Hassan Jameel Asghar Dali Kaafar AAML 34 2 0 12 Apr 2023
Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties Jingwei Sun Zhixu Du Anna Dai Saleh Baghersalimi Alireza Amirshahi David Atienza Yiran Chen FedML 16 7 0 28 Mar 2023
Model Extraction Attacks on Split Federated Learning Jingtao Li Adnan Siraj Rakin Xing Chen Li Yang Zhezhi He Deliang Fan C. Chakrabarti FedML 65 5 0 13 Mar 2023
Physical Adversarial Attacks on Deep Neural Networks for Traffic Sign Recognition: A Feasibility Study Fabian Woitschek G. Schneider AAML 38 9 0 27 Feb 2023
A Plot is Worth a Thousand Words: Model Information Stealing Attacks via Scientific Plots Boyang Zhang Xinlei He Yun Shen Tianhao Wang Yang Zhang AAML 27 2 0 23 Feb 2023
On Function-Coupled Watermarks for Deep Neural Networks Xiangyu Wen Yu Li Weizhen Jiang Qian-Lan Xu AAML 28 1 0 08 Feb 2023
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models Abdullah Çaglar Öksüz Anisa Halimi Erman Ayday ELM AAML 21 2 0 04 Feb 2023
IronForge: An Open, Secure, Fair, Decentralized Federated Learning Guangsheng Yu Xu Wang Caijun Sun Qin Wang Ping Yu Wei Ni R. Liu Xiwei Xu OOD AI4CE 29 25 0 07 Jan 2023
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning A. Salem Giovanni Cherubin David E. Evans Boris Köpf Andrew J. Paverd Anshuman Suri Shruti Tople Santiago Zanella Béguelin 47 35 0 21 Dec 2022
A Survey on Reinforcement Learning Security with Application to Autonomous Driving Ambra Demontis Maura Pintor Luca Demetrio Kathrin Grosse Hsiao-Ying Lin Chengfang Fang Battista Biggio Fabio Roli AAML 42 4 0 12 Dec 2022
Model Extraction Attack against Self-supervised Speech Models Tsung-Yuan Hsu Chen An Li Tung-Yu Wu Hung-yi Lee 27 1 0 29 Nov 2022
Federated Learning Attacks and Defenses: A Survey Yao Chen Yijie Gui Hong Lin Wensheng Gan Yongdong Wu FedML 44 29 0 27 Nov 2022
Data-free Defense of Black Box Models Against Adversarial Attacks Gaurav Kumar Nayak Inder Khatri Ruchit Rawal Anirban Chakraborty AAML 33 1 0 03 Nov 2022
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks Jiyang Guan Jian Liang Ran He AAML MLAU 50 29 0 21 Oct 2022
Free Fine-tuning: A Plug-and-Play Watermarking Scheme for Deep Neural Networks Run Wang Jixing Ren Boheng Li Tianyi She Wenhui Zhang Liming Fang Jing Chen Chao Shen Lina Wang WIGM 32 16 0 14 Oct 2022
Decompiling x86 Deep Neural Network Executables Zhibo Liu Yuanyuan Yuan Shuai Wang Xiaofei Xie L. Ma AAML 45 13 0 03 Oct 2022
Privacy Attacks Against Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models Sohaib Ahmad Benjamin Fuller Kaleel Mahmood AAML 27 0 0 22 Sep 2022
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks Xuanli He Qiongkai Xu Yi Zeng Lingjuan Lyu Fangzhao Wu Jiwei Li R. Jia WaLM 188 72 0 19 Sep 2022
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions Lingjiao Chen Zhihua Jin Sabri Eyuboglu Christopher Ré Matei A. Zaharia James Zou 51 9 0 18 Sep 2022
Orchestrating Collaborative Cybersecurity: A Secure Framework for Distributed Privacy-Preserving Threat Intelligence Sharing J. Troncoso-Pastoriza Alain Mermoud Romain Bouyé Francesco Marino Jean-Philippe Bossuat Vincent Lenders Jean-Pierre Hubaux 32 3 0 06 Sep 2022
AWEncoder: Adversarial Watermarking Pre-trained Encoders in Contrastive Learning Tianxing Zhang Hanzhou Wu Xiaofeng Lu Guangling Sun AAML 27 4 0 08 Aug 2022
MOVE: Effective and Harmless Ownership Verification via Embedded External Features Yiming Li Linghui Zhu Xiaojun Jia Yang Bai Yong Jiang Shutao Xia Xiaochun Cao Kui Ren AAML 44 12 0 04 Aug 2022
Careful What You Wish For: on the Extraction of Adversarially Trained Models Kacem Khaled Gabriela Nicolescu F. Magalhães MIACV AAML 32 4 0 21 Jul 2022
Black-box Generalization of Machine Teaching Xiaofeng Cao Yaming Guo Ivor W. Tsang James T. Kwok 28 0 0 30 Jun 2022
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences Daryna Oliynyk Rudolf Mayer Andreas Rauber 45 106 0 16 Jun 2022