Stealing Hyperparameters in Machine Learning

14 February 2018

Papers citing "Stealing Hyperparameters in Machine Learning"

50 / 206 papers shown

Title
SNIFF: Reverse Engineering of Neural Networks with Fault Attacks J. Breier Dirmanto Jap Xiaolu Hou S. Bhasin Yang Liu 15 52 0 23 Feb 2020
Influence Function based Data Poisoning Attacks to Top-N Recommender Systems Minghong Fang Neil Zhenqiang Gong Jia-Wei Liu TDI 8 154 0 19 Feb 2020
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps Zhichuang Sun Ruimin Sun Long Lu Alan Mislove 31 78 0 18 Feb 2020
Mitigating Query-Flooding Parameter Duplication Attack on Regression Models with High-Dimensional Gaussian Mechanism Xiaoguang Li Hui Li Haonan Yan Zelei Cheng Wenhai Sun Hui Zhu AAML 12 1 0 06 Feb 2020
Model Extraction Attacks against Recurrent Neural Networks Tatsuya Takemura Naoto Yanai T. Fujiwara MLAU MIACV AAML 15 15 0 01 Feb 2020
Adversarial Model Extraction on Graph Neural Networks David DeFazio Arti Ramesh AAML MLAU 12 20 0 16 Dec 2019
Towards Security Threats of Deep Learning Systems: A Survey Yingzhe He Guozhu Meng Kai Chen Xingbo Hu Jinwen He AAML ELM 11 14 0 28 Nov 2019
Survey of Attacks and Defenses on Edge-Deployed Neural Networks Mihailo Isakov V. Gadepally K. Gettings Michel A. Kinsy AAML 12 31 0 27 Nov 2019
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning Minghong Fang Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong AAML OOD FedML 46 1,070 0 26 Nov 2019
CHEETAH: An Ultra-Fast, Approximation-Free, and Privacy-Preserved Neural Network Framework based on Joint Obscure Linear and Nonlinear Computations Qiao Zhang Cong Wang Chunsheng Xin Hongyi Wu 13 4 0 12 Nov 2019
Quantifying (Hyper) Parameter Leakage in Machine Learning Vasisht Duddu D. V. Rao AAML MIACV FedML 28 5 0 31 Oct 2019
MaskedNet: The First Hardware Inference Engine Aiming Power Side-Channel Protection Anuj Dubey Rosario Cammarota Aydin Aysu AAML 16 78 0 29 Oct 2019
IPGuard: Protecting Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong 11 106 0 28 Oct 2019
Secure Evaluation of Quantized Neural Networks Anders Dalskov Daniel E. Escudero Marcel Keller 12 137 0 28 Oct 2019
Piracy Resistant Watermarks for Deep Neural Networks Huiying Li Emily Willson Shawn Shan B. Ye Shehroz S. Khan 26 26 0 02 Oct 2019
Robust Membership Encoding: Inference Attacks and Copyright Protection for Deep Learning Congzheng Song Reza Shokri MIACV 11 5 0 27 Sep 2019
GAMIN: An Adversarial Approach to Black-Box Model Inversion Ulrich Aivodji Sébastien Gambs Timon Ther MLAU 25 42 0 26 Sep 2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 11 383 0 23 Sep 2019
High Accuracy and High Fidelity Extraction of Neural Networks Matthew Jagielski Nicholas Carlini David Berthelot Alexey Kurakin Nicolas Papernot MLAU MIACV 34 370 0 03 Sep 2019
Big Data Analytics for Large Scale Wireless Networks: Challenges and Opportunities Hongning Dai Raymond Chi-Wing Wong Hao Wang Zibin Zheng A. Vasilakos AI4CE GNN 14 65 0 02 Sep 2019
Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems Lea Schonherr Thorsten Eisenhofer Steffen Zeiler Thorsten Holz D. Kolossa AAML 41 63 0 05 Aug 2019
Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods Arif Siddiqi AAML 11 11 0 17 Jul 2019
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks Tribhuvanesh Orekondy Bernt Schiele Mario Fritz AAML 9 164 0 26 Jun 2019
On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks Masoumeh Shafieinejad Jiaqi Wang Nils Lukas Xinda Li Florian Kerschbaum AAML 22 8 0 18 Jun 2019
Membership Privacy for Machine Learning Models Through Knowledge Transfer Virat Shejwalkar Amir Houmansadr 14 10 0 15 Jun 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 6 235 0 24 May 2019
A framework for the extraction of Deep Neural Networks by leveraging public data Soham Pal Yash Gupta Aditya Shukla Aditya Kanade S. Shevade V. Ganapathy FedML MLAU MIACV 19 56 0 22 May 2019
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges Rob Ashmore R. Calinescu Colin Paterson AI4TS 21 116 0 10 May 2019
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning A. Salem Apratim Bhattacharyya Michael Backes Mario Fritz Yang Zhang FedML AAML MIACV 17 250 0 01 Apr 2019
Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints Xing Hu Ling Liang Lei Deng Shuangchen Li Xinfeng Xie Yu Ji Yufei Ding Chang Liu T. Sherwood Yuan Xie AAML MLAU 21 36 0 10 Mar 2019
Attacking Graph-based Classification via Manipulating the Graph Structure Binghui Wang Neil Zhenqiang Gong AAML 24 152 0 01 Mar 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David E. Evans 13 7 0 24 Feb 2019
Stealing Neural Networks via Timing Side Channels Vasisht Duddu D. Samanta D. V. Rao V. Balas AAML MLAU FedML 20 133 0 31 Dec 2018
Privacy Partitioning: Protecting User Data During the Deep Learning Inference Phase Jianfeng Chi Emmanuel Owusu Xuwang Yin Tong Yu William Chan P. Tague Yuan Tian FedML 17 28 0 07 Dec 2018
Knockoff Nets: Stealing Functionality of Black-Box Models Tribhuvanesh Orekondy Bernt Schiele Mario Fritz MLAU 6 525 0 06 Dec 2018
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV AAML 13 243 0 03 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 188 272 0 03 Dec 2018
Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems Bashir Rastegarpanah Krishna P. Gummadi M. Crovella 16 119 0 02 Dec 2018
Exploring Connections Between Active Learning and Model Extraction Varun Chandrasekaran Kamalika Chaudhuri Irene Giacomelli Shane Walker Songbai Yan MIACV 14 157 0 05 Nov 2018
Auditing Data Provenance in Text-Generation Models Congzheng Song Vitaly Shmatikov MLAU 9 17 0 01 Nov 2018
Security Matters: A Survey on Adversarial Machine Learning Guofu Li Pengjia Zhu Jin Li Zhemin Yang Ning Cao Zhiyi Chen AAML 16 24 0 16 Oct 2018
Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks Sanghyun Hong Michael Davinroy Yigitcan Kaya S. Locke Ian Rackow Kevin Kulda Dana Dachman-Soled Tudor Dumitras MIACV 25 90 0 08 Oct 2018
Data-Driven Debugging for Functional Side Channels Saeid Tizpaz-Niari Pavol Cerný Ashutosh Trivedi 14 14 0 30 Aug 2018
Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding Lea Schonherr Katharina Kohls Steffen Zeiler Thorsten Holz D. Kolossa AAML 22 285 0 16 Aug 2018
Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures Mengjia Yan Christopher W. Fletcher Josep Torrellas MIACV FedML 15 244 0 14 Aug 2018
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service L. Hanzlik Yang Zhang Kathrin Grosse A. Salem Maximilian Augustin Michael Backes Mario Fritz OffRL 14 103 0 01 Aug 2018
Security and Privacy Issues in Deep Learning Ho Bae Jaehee Jang Dahuin Jung Hyemi Jang Heonseok Ha Hyungyu Lee Sungroh Yoon SILM MIACV 38 77 0 31 Jul 2018
Machine Learning with Membership Privacy using Adversarial Regularization Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV 6 465 0 16 Jul 2018
Privacy-preserving Machine Learning through Data Obfuscation Tianwei Zhang Zecheng He R. Lee 12 79 0 05 Jul 2018
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models A. Salem Yang Zhang Mathias Humbert Pascal Berrang Mario Fritz Michael Backes MIACV MIALM 16 925 0 04 Jun 2018