Membership Inference Attacks against Machine Learning Models

18 October 2016

Papers citing "Membership Inference Attacks against Machine Learning Models"

50 / 2,056 papers shown

Title
On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping Sanghyun Hong Varun Chandrasekaran Yigitcan Kaya Tudor Dumitras Nicolas Papernot AAML 28 136 0 26 Feb 2020
Approximate Data Deletion from Machine Learning Models Zachary Izzo Mary Anne Smart Kamalika Chaudhuri James Zou MU 22 251 0 24 Feb 2020
Stealing Black-Box Functionality Using The Deep Neural Tree Architecture Daniel Teitelman I. Naeh Shie Mannor 11 5 0 23 Feb 2020
SNIFF: Reverse Engineering of Neural Networks with Fault Attacks J. Breier Dirmanto Jap Xiaolu Hou S. Bhasin Yang Liu 17 53 0 23 Feb 2020
Optimizing Privacy-Preserving Outsourced Convolutional Neural Network Predictions Minghui Li Sherman S. M. Chow Shengshan Hu Yuejing Yan Minxin Du Peng Kuang 6 45 0 22 Feb 2020
Anonymizing Data for Privacy-Preserving Federated Learning Olivia Choudhury A. Gkoulalas-Divanis Theodoros Salonidis I. Sylla Yoonyoung Park Grace Hsu Amar K. Das FedML 30 42 0 21 Feb 2020
Data Heterogeneity Differential Privacy: From Theory to Algorithm Yilin Kang Jian Li Yong Liu Weiping Wang 28 1 0 20 Feb 2020
Input Perturbation: A New Paradigm between Central and Local Differential Privacy Yilin Kang Yong Liu Ben Niu Xin-Yi Tong Likun Zhang Weiping Wang 27 11 0 20 Feb 2020
PrivacyFL: A simulator for privacy-preserving and secure federated learning Vaikkunth Mugunthan Anton Peraire-Bueno Lalana Kagal FedML 16 57 0 19 Feb 2020
Influence Function based Data Poisoning Attacks to Top-N Recommender Systems Minghong Fang Neil Zhenqiang Gong Jia-Wei Liu TDI 18 154 0 19 Feb 2020
Data and Model Dependencies of Membership Inference Attack Shakila Mahjabin Tonni Dinusha Vatsalan F. Farokhi Dali Kaafar Zhigang Lu Gioacchino Tangari 11 17 0 17 Feb 2020
Classifying the classifier: dissecting the weight space of neural networks Gabriel Eilertsen Daniel Jonsson Timo Ropinski Jonas Unger Anders Ynnerman 11 53 0 13 Feb 2020
Wireless Federated Learning with Local Differential Privacy Mohamed Seif Ravi Tandon Ming Li 84 171 0 12 Feb 2020
Salvaging Federated Learning by Local Adaptation Tao Yu Eugene Bagdasaryan Vitaly Shmatikov FedML 25 261 0 12 Feb 2020
Security and Privacy in IoT Using Machine Learning and Blockchain: Threats & Countermeasures Nazar Waheed Xiangjian He Muhammad Ikram Muhammad Usman Saad Sajid Hashmi Muhammad Usman 24 6 0 10 Feb 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 114 130 0 07 Feb 2020
Adversarial Machine Learning -- Industry Perspectives Ramnath Kumar Magnus Nyström J. Lambert Andrew Marshall Mario Goertzel Andi Comissoneru Matt Swann Sharon Xia AAML SILM 29 232 0 04 Feb 2020
Radioactive data: tracing through training Alexandre Sablayrolles Matthijs Douze Cordelia Schmid Hervé Jégou 38 74 0 03 Feb 2020
Interpretability of Blackbox Machine Learning Models through Dataview Extraction and Shadow Model creation Rupam Patir Shubham Singhal C. Anantaram Vikram Goyal 16 0 0 02 Feb 2020
NASS: Optimizing Secure Inference via Neural Architecture Search S. Bian Weiwen Jiang Qing Lu Yiyu Shi Takashi Sato 21 25 0 30 Jan 2020
Modelling and Quantifying Membership Information Leakage in Machine Learning F. Farokhi M. Kâafar AAML FedML MIACV 56 24 0 29 Jan 2020
DP-CGAN: Differentially Private Synthetic Data and Label Generation Reihaneh Torkzadehmahani Peter Kairouz B. Paten SyDa 25 235 0 27 Jan 2020
CorGAN: Correlation-Capturing Convolutional Generative Adversarial Networks for Generating Synthetic Healthcare Records A. Torfi Edward A. Fox SyDa 27 58 0 25 Jan 2020
TiFL: A Tier-based Federated Learning System Zheng Chai Ahsan Ali Syed Zawad Stacey Truex Ali Anwar Nathalie Baracaldo Yi Zhou Heiko Ludwig Feng Yan Yue Cheng FedML 27 275 0 25 Jan 2020
Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack Bo Zhang Ruotong Yu Haipei Sun Yanying Li Jun Xu Wendy Hui Wang AAML 22 13 0 24 Jan 2020
On the Resilience of Biometric Authentication Systems against Random Inputs Benjamin Zi Hao Zhao Hassan Jameel Asghar M. Kâafar AAML 39 23 0 13 Jan 2020
Membership Inference Attacks Against Object Detection Models Yeachan Park Myung-joo Kang MIACV 29 6 0 12 Jan 2020
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Shuang Song Kunal Talwar Abhradeep Thakurta 29 83 0 10 Jan 2020
Transferability of Adversarial Examples to Attack Cloud-based Image Classifier Service Dou Goodman SILM AAML 11 10 0 08 Jan 2020
Assessing differentially private deep learning with Membership Inference Daniel Bernau Philip-William Grassal J. Robl Florian Kerschbaum MIACV FedML 26 23 0 24 Dec 2019
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer Hong Chang Virat Shejwalkar Reza Shokri Amir Houmansadr FedML 26 167 0 24 Dec 2019
Privacy Attacks on Network Embeddings Michael Ellers Michael Cochez Tobias Schumacher M. Strohmaier Florian Lemmerich AAML 19 12 0 23 Dec 2019
secml: A Python Library for Secure and Explainable Machine Learning Maura Pintor Christian Scano Angelo Sotgiu Marco Melis Ambra Demontis Battista Biggio AAML 23 15 0 20 Dec 2019
Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation Yang He Shadi Rahimian Bernt Schiele Mario Fritz MIACV 21 49 0 20 Dec 2019
Learning to Prevent Leakage: Privacy-Preserving Inference in the Mobile Cloud Shuang Zhang Liyao Xiang Congcong Li Yixuan Wang Quanshi Zhang Zeyu Liu Bo-wen Li FedML 16 1 0 18 Dec 2019
Analyzing Information Leakage of Updates to Natural Language Models Santiago Zanella Béguelin Lukas Wutschitz Shruti Tople Victor Rühle Andrew Paverd O. Ohrimenko Boris Köpf Marc Brockschmidt ELM MIACV FedML PILM KELM 8 125 0 17 Dec 2019
Asynchronous Federated Learning with Differential Privacy for Edge Intelligence Yanan Li Shusen Yang Xuebin Ren Cong Zhao FedML 19 33 0 17 Dec 2019
Efficient Per-Example Gradient Computations in Convolutional Neural Networks G. Rochette Andre Manoel Eric W. Tramel 19 19 0 12 Dec 2019
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning Runhua Xu Nathalie Baracaldo Yi Zhou Ali Anwar Heiko Ludwig FedML 24 287 0 12 Dec 2019
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 76 6,103 0 10 Dec 2019
Privacy-Preserving Blockchain Based Federated Learning with Differential Data Sharing Anudit Nagar 16 21 0 10 Dec 2019
Machine Unlearning Lucas Bourtoule Varun Chandrasekaran Christopher A. Choquette-Choo Hengrui Jia Adelin Travers Baiwu Zhang David Lie Nicolas Papernot MU 65 815 0 09 Dec 2019
Towards Security Threats of Deep Learning Systems: A Survey Yingzhe He Guozhu Meng Kai Chen Xingbo Hu Jinwen He AAML ELM 15 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 22 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 60 1,077 0 26 Nov 2019
Gradient Perturbation is Underrated for Differentially Private Convex Optimization Da Yu Huishuai Zhang Kwei-Herng Lai Yuening Li Xia Hu 23 37 0 26 Nov 2019
PAC learning with stable and private predictions Y. Dagan Vitaly Feldman 20 12 0 24 Nov 2019
Federated Learning with Bayesian Differential Privacy Aleksei Triastcyn Boi Faltings FedML 19 174 0 22 Nov 2019
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability Stacey Truex Ling Liu Mehmet Emre Gursoy Wenqi Wei Lei Yu MIACV 32 46 0 21 Nov 2019
Can You Really Backdoor Federated Learning? Ziteng Sun Peter Kairouz A. Suresh H. B. McMahan FedML 15 562 0 18 Nov 2019