Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey

13 May 2021

Papers citing "Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey"

50 / 60 papers shown

Title
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 103 3 0 20 Nov 2023
Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey Yuantian Miao Chao Chen Lei Pan Qing-Long Han Jun Zhang Yang Xiang AAML 77 68 0 16 Feb 2021
Property Inference From Poisoning Melissa Chase Esha Ghosh Saeed Mahloujifar MIACV 70 80 0 26 Jan 2021
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators Dingfan Chen Tribhuvanesh Orekondy Mario Fritz SyDa 54 185 0 15 Jun 2020
Entangled Watermarks as a Defense against Model Extraction Hengrui Jia Christopher A. Choquette-Choo Varun Chandrasekaran Nicolas Papernot WaLM AAML 67 219 0 27 Feb 2020
Extraction of Complex DNN Models: Real Threat or Boogeyman? B. Atli S. Szyller Mika Juuti Samuel Marchal Nadarajah Asokan MLAU MIACV 54 45 0 11 Oct 2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 64 390 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 81 377 0 03 Sep 2019
Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing Yang Liu Zhuo Ma Ximeng Liu Siqi Ma Surya Nepal R. Deng FedML 53 63 0 24 Jul 2019
QUOTIENT: Two-Party Secure Neural Network Training and Prediction Nitin Agrawal Ali Shahin Shamsabadi Matt J. Kusner Adria Gascon 60 216 0 08 Jul 2019
DAWN: Dynamic Adversarial Watermarking of Neural Networks S. Szyller B. Atli Samuel Marchal Nadarajah Asokan MLAU AAML 45 179 0 03 Jun 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 42 241 0 24 May 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 48 46 0 25 Mar 2019
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment Ziqi Yang E. Chang Zhenkai Liang MLAU 54 60 0 22 Feb 2019
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss Nicholas Frosst Nicolas Papernot Geoffrey E. Hinton 50 160 0 05 Feb 2019
Knockoff Nets: Stealing Functionality of Black-Box Models Tribhuvanesh Orekondy Bernt Schiele Mario Fritz MLAU 95 534 0 06 Dec 2018
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models Sven Gowal Krishnamurthy Dvijotham Robert Stanforth Rudy Bunel Chongli Qin J. Uesato Relja Arandjelović Timothy A. Mann Pushmeet Kohli AAML 76 556 0 30 Oct 2018
Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection Xiao Chen Chaoran Li Derui Wang S. Wen Jun Zhang Surya Nepal Yang Xiang K. Ren AAML 57 245 0 10 Aug 2018
Machine Learning with Membership Privacy using Adversarial Regularization Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV 47 471 0 16 Jul 2018
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service Amartya Sanyal Matt J. Kusner Adria Gascon Varun Kanade FedML 63 127 0 09 Jun 2018
Blind Justice: Fairness with Encrypted Sensitive Attributes Niki Kilbertus Adria Gascon Matt J. Kusner Michael Veale Krishna P. Gummadi Adrian Weller 55 151 0 08 Jun 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 93 948 0 04 Jun 2018
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning Jinyuan Jia Neil Zhenqiang Gong AAML 60 164 0 13 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 142 1,474 0 10 May 2018
PRADA: Protecting against DNN Model Stealing Attacks Mika Juuti S. Szyller Samuel Marchal Nadarajah Asokan SILM AAML 68 442 0 07 May 2018
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition Pete Warden 74 1,616 0 09 Apr 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 125 138 0 27 Feb 2018
Stealing Hyperparameters in Machine Learning Binghui Wang Neil Zhenqiang Gong AAML 136 466 0 14 Feb 2018
Digital Watermarking for Deep Neural Networks Yuki Nagai Yusuke Uchida S. Sakazawa Shiníchi Satoh WIGM 53 144 0 06 Feb 2018
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications M. Riazi Christian Weinert Oleksandr Tkachenko Ebrahim M. Songhori T. Schneider F. Koushanfar FedML 46 494 0 10 Jan 2018
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 123 1,501 0 02 Nov 2017
Machine Learning Models that Remember Too Much Congzheng Song Thomas Ristenpart Vitaly Shmatikov VLM 70 516 0 22 Sep 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 280 8,878 0 25 Aug 2017
Knock Knock, Who's There? Membership Inference on Aggregate Location Data Apostolos Pyrgelis Carmela Troncoso Emiliano De Cristofaro MIACV 101 271 0 21 Aug 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 155 2,151 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 304 12,063 0 19 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,906 0 22 May 2017
Information Leakage Games Mário S. Alvim K. Chatzikokolakis Yusuke Kawamoto C. Palamidessi AAML 37 21 0 14 May 2017
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 146 2,733 0 13 Apr 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 115 1,401 0 24 Feb 2017
An Adversarial Regularisation for Semi-Supervised Training of Structured Output Neural Networks Mateusz Koziñski Loïc Simon F. Jurie GAN 46 18 0 08 Feb 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 336 4,626 0 10 Nov 2016
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 246 4,122 0 18 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 104 1,805 0 09 Sep 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 201 6,121 0 01 Jul 2016
Adversarially Learned Inference Vincent Dumoulin Ishmael Belghazi Ben Poole Olivier Mastropietro Alex Lamb Martín Arjovsky Aaron Courville GAN 72 1,314 0 02 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,976 0 16 Feb 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,677 0 08 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,878 0 10 Dec 2015
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin Dario Amodei Rishita Anubhai Eric Battenberg Carl Case Jared Casper ... Chong-Jun Wang Bo Xiao Dani Yogatama J. Zhan Zhenyao Zhu 120 2,972 0 08 Dec 2015