Stealing Machine Learning Models via Prediction APIs

9 September 2016

Papers citing "Stealing Machine Learning Models via Prediction APIs"

50 / 344 papers shown

Title
Finding Meaningful Distributions of ML Black-boxes under Forensic Investigation Jiyi Zhang Hansheng Fang Hwee Kuan Lee E. Chang 35 1 0 10 May 2023
GTree: GPU-Friendly Privacy-preserving Decision Tree Training and Inference Qifan Wang Shujie Cui Lei Zhou Ye Dong Jianli Bai Yun Sing Koh Giovanni Russello 33 0 0 01 May 2023
Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks Isabell Lederer Rudolf Mayer Andreas Rauber 34 19 0 22 Apr 2023
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings Asim Waheed Vasisht Duddu Nadarajah Asokan 40 9 0 17 Apr 2023
On the Adversarial Inversion of Deep Biometric Representations Gioacchino Tangari Shreesh Keskar Hassan Jameel Asghar Dali Kaafar AAML 47 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 21 8 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
Decision-BADGE: Decision-based Adversarial Batch Attack with Directional Gradient Estimation Geunhyeok Yu Minwoo Jeon Hyoseok Hwang AAML 26 1 0 09 Mar 2023
Students Parrot Their Teachers: Membership Inference on Model Distillation Matthew Jagielski Milad Nasr Christopher A. Choquette-Choo Katherine Lee Nicholas Carlini FedML 46 21 0 06 Mar 2023
Adversarial Sampling for Fairness Testing in Deep Neural Network Tosin Ige William Marfo Justin Tonkinson Sikiru Adewale Bolanle Hafiz Matti OOD 26 9 0 06 Mar 2023
Adversarial Attacks on Machine Learning in Embedded and IoT Platforms Christian Westbrook S. Pasricha AAML 25 3 0 03 Mar 2023
AdvRain: Adversarial Raindrops to Attack Camera-based Smart Vision Systems Amira Guesmi Muhammad Abdullah Hanif Mohamed Bennai AAML 56 17 0 02 Mar 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 37 2 0 23 Feb 2023
AutoML in The Wild: Obstacles, Workarounds, and Expectations Yuan Sun Qiurong Song Xinning Gui Fenglong Ma Ting Wang 26 13 0 21 Feb 2023
Digital Privacy Under Attack: Challenges and Enablers Baobao Song Mengyue Deng Shiva Raj Pokhrel Qiujun Lan R. Doss Gang Li AAML 39 3 0 18 Feb 2023
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models Abdullah Çaglar Öksüz Anisa Halimi Erman Ayday ELM AAML 23 2 0 04 Feb 2023
A Survey on Digital Twins: Architecture, Enabling Technologies, Security and Privacy, and Future Prospects Yuntao Wang Zhou Su Shaolong Guo Minghui Dai Tom H. Luan Yiliang Liu 29 108 0 31 Jan 2023
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks Jona Klemenc Holger Trittenbach AAML 32 1 0 28 Jan 2023
Threats, Vulnerabilities, and Controls of Machine Learning Based Systems: A Survey and Taxonomy Yusuke Kawamoto Kazumasa Miyake K. Konishi Y. Oiwa 29 4 0 18 Jan 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
A Comparative Study of Image Disguising Methods for Confidential Outsourced Learning Sagar Sharma Yuechun Gu Keke Chen 39 0 0 31 Dec 2022
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 38 75 0 29 Dec 2022
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning A. Salem Giovanni Cherubin David Evans Boris Köpf Andrew Paverd Anshuman Suri Shruti Tople Santiago Zanella Béguelin 52 35 0 21 Dec 2022
Learned Systems Security R. Schuster Jinyi Zhou Thorsten Eisenhofer Paul Grubbs Nicolas Papernot AAML 24 2 0 20 Dec 2022
Review of security techniques for memristor computing systems Minhui Zou Nan Du Shahar Kvatinsky AAML 24 7 0 19 Dec 2022
A Survey on Reinforcement Learning Security with Application to Autonomous Driving Ambra Demontis Maura Pintor Christian Scano Kathrin Grosse Hsiao-Ying Lin Chengfang Fang Battista Biggio Fabio Roli AAML 49 4 0 12 Dec 2022
Confidential High-Performance Computing in the Public Cloud Keke Chen FedML 19 6 0 05 Dec 2022
Model Extraction Attack against Self-supervised Speech Models Tsung-Yuan Hsu Chen-An Li Tung-Yu Wu Hung-yi Lee 32 1 0 29 Nov 2022
Federated Learning Attacks and Defenses: A Survey Yao Chen Yijie Gui Hong Lin Wensheng Gan Yongdong Wu FedML 49 29 0 27 Nov 2022
A Brief Overview of AI Governance for Responsible Machine Learning Systems Navdeep Gill Abhishek Mathur Marcos V. Conde 29 5 0 21 Nov 2022
On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target Models Mauro Conti Jiaxin Li S. Picek MIALM 37 2 0 28 Oct 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 41 2 0 28 Oct 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 27 14 0 27 Oct 2022
Desiderata for next generation of ML model serving Sherif Akoush Andrei Paleyes A. V. Looveren Clive Cox 38 5 0 26 Oct 2022
New data poison attacks on machine learning classifiers for mobile exfiltration M. A. Ramírez Sangyoung Yoon Ernesto Damiani H. A. Hamadi C. Ardagna Nicola Bena Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 38 4 0 20 Oct 2022
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey Huiyun Cao Wenlong Zou Yinkun Wang Ting Song Mengjun Liu AAML 56 5 0 19 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Yifan Yang 48 20 0 18 Oct 2022
Industry-Scale Orchestrated Federated Learning for Drug Discovery M. Oldenhof G. Ács Balázs Pejó A. Schuffenhauer Nicholas Holway ... Yves Moreau Ola Engkvist Hugo Ceulemans Camille Marini M. Galtier FedML 43 38 0 17 Oct 2022
Decompiling x86 Deep Neural Network Executables Zhibo Liu Yuanyuan Yuan Shuai Wang Xiaofei Xie Lei 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 56 9 0 18 Sep 2022
Dataset Inference for Self-Supervised Models Adam Dziedzic Haonan Duan Muhammad Ahmad Kaleem Nikita Dhawan Jonas Guan Yannis Cattan Franziska Boenisch Nicolas Papernot 42 26 0 16 Sep 2022
Model Inversion Attacks against Graph Neural Networks Zaixin Zhang Qi Liu Zhenya Huang Hao Wang Cheekong Lee Enhong AAML 28 35 0 16 Sep 2022
SEEK: model extraction attack against hybrid secure inference protocols Si-Quan Chen Junfeng Fan MIACV 16 2 0 14 Sep 2022
Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots Waiman Si Michael Backes Jeremy Blackburn Emiliano De Cristofaro Gianluca Stringhini Savvas Zannettou Yang Zhang 41 58 0 07 Sep 2022
Joint Linear and Nonlinear Computation across Functions for Efficient Privacy-Preserving Neural Network Inference Qiao Zhang Tao Xiang Chunsheng Xin Biwen Chen Hongyi Wu 39 1 0 04 Sep 2022
Membership Inference Attacks by Exploiting Loss Trajectory Yiyong Liu Zhengyu Zhao Michael Backes Yang Zhang 27 98 0 31 Aug 2022
Demystifying Arch-hints for Model Extraction: An Attack in Unified Memory System Zhendong Wang Xiaoming Zeng Xulong Tang Danfeng Zhang Xingbo Hu Yang Hu AAML MIACV FedML 32 6 0 29 Aug 2022
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy Wenqiang Ruan Ming Xu Wenjing Fang Li Wang Lei Wang Wei Han 42 12 0 18 Aug 2022