Membership Inference Attacks against Machine Learning Models

18 October 2016

Papers citing "Membership Inference Attacks against Machine Learning Models"

50 / 2,053 papers shown

Title
F-BLEAU: Fast Black-box Leakage Estimation Giovanni Cherubin K. Chatzikokolakis C. Palamidessi 18 34 0 04 Feb 2019
Utility Preserving Secure Private Data Release J. Dhaliwal Geoffrey So Aleatha Parker-Wood Mélanie Beck 14 2 0 28 Jan 2019
Bayesian Differential Privacy for Machine Learning Aleksei Triastcyn Boi Faltings 28 2 0 28 Jan 2019
Interpretable Complex-Valued Neural Networks for Privacy Protection Liyao Xiang Haotian Ma Hao Zhang Yifan Zhang Jie Ren Quanshi Zhang AAML 14 32 0 28 Jan 2019
Detecting Overfitting of Deep Generative Networks via Latent Recovery Ryan Webster Julien Rabin Loïc Simon F. Jurie GAN 14 99 0 09 Jan 2019
Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data Lorenzo Frigerio Anderson Santana de Oliveira L. Gomez Patrick Duverger SyDa AI4TS 28 110 0 08 Jan 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 17 74 0 08 Jan 2019
Adversarial Examples Versus Cloud-based Detectors: A Black-box Empirical Study Xurong Li S. Ji Men Han Juntao Ji Zhenyu Ren Yushan Liu Chunming Wu AAML 21 31 0 04 Jan 2019
Please Forget Where I Was Last Summer: The Privacy Risks of Public Location (Meta)Data Kostas Drakonakis Panagiotis Ilia S. Ioannidis Jason Polakis 6 29 0 03 Jan 2019
Stealing Neural Networks via Timing Side Channels Vasisht Duddu D. Samanta D. V. Rao V. Balas AAML MLAU FedML 27 133 0 31 Dec 2018
Privacy-Preserving Collaborative Deep Learning with Unreliable Participants Lingchen Zhao Qian Wang Qin Zou Yan Zhang Yanjiao Chen FedML 10 9 0 25 Dec 2018
Reaching Data Confidentiality and Model Accountability on the CalTrain Zhongshu Gu Hani Jamjoom D. Su Heqing Huang Jialong Zhang Tengfei Ma Dimitrios E. Pendarakis Ian Molloy FedML 11 15 0 07 Dec 2018
A Hybrid Approach to Privacy-Preserving Federated Learning Stacey Truex Nathalie Baracaldo Ali Anwar Thomas Steinke Heiko Ludwig Rui Zhang Yi Zhou FedML 19 884 0 07 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 19 28 0 07 Dec 2018
Knockoff Nets: Stealing Functionality of Black-Box Models Tribhuvanesh Orekondy Bernt Schiele Mario Fritz MLAU 22 526 0 06 Dec 2018
Differentially Private Data Generative Models Qingrong Chen Chong Xiang Minhui Xue Bo-wen Li Nikita Borisov Dali Kaafar Haojin Zhu SyDa AAML 15 79 0 06 Dec 2018
Privacy-Preserving Distributed Deep Learning for Clinical Data Brett K. Beaulieu-Jones W. Yuan S. G. Finlayson Zhiwei Steven Wu OOD FedML 17 46 0 04 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 13 244 0 03 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 194 275 0 03 Dec 2018
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning Peng Kuang Mengkai Song Zhifei Zhang Yang Song Qian Wang Hairong Qi FedML 28 776 0 03 Dec 2018
An overview of deep learning in medical imaging focusing on MRI A. Lundervold A. Lundervold OOD 17 1,605 0 25 Nov 2018
Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning Muhammad Shayan Clement Fung Chris J. M. Yoon Ivan Beschastnikh FedML 8 81 0 24 Nov 2018
Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting Clement Fung Jamie Koerner Stewart Grant Ivan Beschastnikh OOD FedML 10 12 0 23 Nov 2018
FALCON: A Fourier Transform Based Approach for Fast and Secure Convolutional Neural Network Predictions Shaohua Li Kaiping Xue Chenkai Ding Xindi Gao David S. L. Wei Tao Wan F. Wu 22 67 0 20 Nov 2018
Boosting Model Performance through Differentially Private Model Aggregation Sophia Collet Robert Dadashi Z. Karam Chang-rui Liu Parinaz Sobhani Yevgeniy Vahlis Ji Chao Zhang FedML 6 1 0 12 Nov 2018
A First Look at Deep Learning Apps on Smartphones Mengwei Xu Jiawei Liu Yuanqiang Liu F. Lin Yunxin Liu Xuanzhe Liu HAI 33 177 0 08 Nov 2018
AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning K. Makarychev Pascal Dupré Yury Makarychev Giancarlo Pellegrino Dan Boneh AAML 29 64 0 08 Nov 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
FAdeML: Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning Faiq Khalid Muhammad Abdullah Hanif Semeen Rehman Junaid Qadir Muhammad Shafique AAML 6 34 0 04 Nov 2018
TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks Faiq Khalid Muhammad Abdullah Hanif Semeen Rehman Rehan Ahmed Muhammad Shafique AAML 22 21 0 02 Nov 2018
Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks Davide Maiorca Battista Biggio Giorgio Giacinto AAML 19 47 0 02 Nov 2018
Auditing Data Provenance in Text-Generation Models Congzheng Song Vitaly Shmatikov MLAU 9 17 0 01 Nov 2018
The Faults in Our Pi Stars: Security Issues and Open Challenges in Deep Reinforcement Learning Vahid Behzadan Arslan Munir 11 27 0 23 Oct 2018
CSI Neural Network: Using Side-channels to Recover Your Artificial Neural Network Information L. Batina S. Bhasin Dirmanto Jap S. Picek AAML 9 65 0 22 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
Privado: Practical and Secure DNN Inference with Enclaves Karan Grover Shruti Tople Shweta Shinde Ranjita Bhagwan Ramachandran Ramjee FedML SILM 15 46 0 01 Oct 2018
Adversarial Attacks and Defences: A Survey Anirban Chakraborty Manaar Alam Vishal Dey Anupam Chattopadhyay Debdeep Mukhopadhyay AAML OOD 23 674 0 28 Sep 2018
Déjà Vu: an empirical evaluation of the memorization properties of ConvNets Alexandre Sablayrolles Matthijs Douze Cordelia Schmid Hervé Jégou 13 18 0 17 Sep 2018
Privacy-Preserving Deep Learning via Weight Transmission L. T. Phong T. Phuong FedML 14 87 0 10 Sep 2018
DP-ADMM: ADMM-based Distributed Learning with Differential Privacy Zonghao Huang Rui Hu Yuanxiong Guo Eric Chan-Tin Yanmin Gong FedML 11 193 0 30 Aug 2018
Data Poisoning Attacks against Online Learning Yizhen Wang Kamalika Chaudhuri AAML 11 92 0 27 Aug 2018
Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures Mengjia Yan Christopher W. Fletcher Josep Torrellas MIACV FedML 37 245 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 16 103 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 45 77 0 31 Jul 2018
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security M. Al-garadi Amr M. Mohamed A. Al-Ali Xiaojiang Du Mohsen Guizani 19 804 0 29 Jul 2018
Machine Learning with Membership Privacy using Adversarial Regularization Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV 13 466 0 16 Jul 2018
Model Reconstruction from Model Explanations S. Milli Ludwig Schmidt Anca Dragan Moritz Hardt FAtt 21 177 0 13 Jul 2018
Algorithms that Remember: Model Inversion Attacks and Data Protection Law Michael Veale Reuben Binns L. Edwards 16 191 0 12 Jul 2018
Privacy-preserving Machine Learning through Data Obfuscation Tianwei Zhang Zecheng He R. Lee 14 79 0 05 Jul 2018
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors Joshua Allen Bolin Ding Janardhan Kulkarni Harsha Nori O. Ohrimenko Sergey Yekhanin SyDa FedML 27 32 0 02 Jul 2018