Knock Knock, Who's There? Membership Inference on Aggregate Location Data

21 August 2017

Papers citing "Knock Knock, Who's There? Membership Inference on Aggregate Location Data"

8 / 58 papers shown

Title
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
The Long Road to Computational Location Privacy: A Survey Vincent Primault A. Boutet Sonia Ben Mokhtar L. Brunie 32 141 0 08 Oct 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 41 928 0 04 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
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 87 1,455 0 10 May 2018
When the signal is in the noise: Exploiting Diffix's Sticky Noise Andrea Gadotti F. Houssiau Luc Rocher B. Livshits Yves-Alexandre de Montjoye 9 20 0 18 Apr 2018
Stealing Hyperparameters in Machine Learning Binghui Wang Neil Zhenqiang Gong AAML 48 458 0 14 Feb 2018
Tagvisor: A Privacy Advisor for Sharing Hashtags Yang Zhang Mathias Humbert Tahleen A. Rahman Cheng-Te Li Jun Pang Michael Backes 26 43 0 12 Feb 2018