Can Two Walk Together: Privacy Enhancing Methods and Preventing Tracking of Users

6 April 2020

Papers citing "Can Two Walk Together: Privacy Enhancing Methods and Preventing Tracking of Users"

8 / 8 papers shown

Title
Privately detecting changes in unknown distributions Rachel Cummings Sara Krehbiel Yuliia Lut Wanrong Zhang OOD 50 11 0 03 Oct 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 199 430 0 29 Nov 2018
Differentially Private Change-Point Detection Rachel Cummings Sara Krehbiel Y. Mei Rui Tuo Wanrong Zhang 46 30 0 29 Aug 2018
Local Differential Privacy for Evolving Data Matthew Joseph Aaron Roth Jonathan R. Ullman Bo Waggoner 88 87 0 20 Feb 2018
Collecting Telemetry Data Privately Bolin Ding Janardhan Kulkarni Sergey Yekhanin 58 689 0 05 Dec 2017
Local, Private, Efficient Protocols for Succinct Histograms Raef Bassily Adam D. Smith FedML 73 458 0 18 Apr 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 109 2,001 0 25 Jul 2014
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 137 1,474 0 06 Mar 2008