ML-Leaks: Model and Data Independent Membership Inference Attacks and
Defenses on Machine Learning Models

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

4 June 2018

Mathias Humbert

Mario Fritz

Michael Backes

Papers citing "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"

15 / 465 papers shown

Title
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning A. Salem Apratim Bhattacharyya Michael Backes Mario Fritz Yang Zhang FedML AAML MIACV 19 250 0 01 Apr 2019
How to Prove Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN Zheng Li Chengyu Hu Yang Zhang Shanqing Guo AAML 16 170 0 05 Mar 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David Evans 15 7 0 24 Feb 2019
Measuring Membership Privacy on Aggregate Location Time-Series Apostolos Pyrgelis Carmela Troncoso Emiliano De Cristofaro 27 23 0 20 Feb 2019
Stealing Neural Networks via Timing Side Channels Vasisht Duddu D. Samanta D. V. Rao V. Balas AAML MLAU FedML 33 133 0 31 Dec 2018
Knockoff Nets: Stealing Functionality of Black-Box Models Tribhuvanesh Orekondy Bernt Schiele Mario Fritz MLAU 24 526 0 06 Dec 2018
Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning Muhammad Shayan Clement Fung Chris J. M. Yoon Ivan Beschastnikh FedML 16 81 0 24 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 27 67 0 20 Nov 2018
Security for Machine Learning-based Systems: Attacks and Challenges during Training and Inference Faiq Khalid Muhammad Abdullah Hanif Semeen Rehman Mohamed Bennai AAML 6 22 0 05 Nov 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 19 103 0 01 Aug 2018
Privacy-preserving Machine Learning through Data Obfuscation Tianwei Zhang Zecheng He R. Lee 20 79 0 05 Jul 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 114 395 0 08 Jun 2018
Killing four birds with one Gaussian process: the relation between different test-time attacks Kathrin Grosse M. Smith Michael Backes AAML 18 2 0 06 Jun 2018
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning Tribhuvanesh Orekondy Seong Joon Oh Yang Zhang Bernt Schiele Mario Fritz PICV FedML 359 37 0 15 May 2018
Towards Plausible Graph Anonymization Yang Zhang Mathias Humbert Bartlomiej Surma Praveen Manoharan Jilles Vreeken Michael Backes 11 20 0 15 Nov 2017