58 citations · 127 across the 7 of their papers we have counts for
7 papers
"Having Confidence in My Confidence Intervals": How Data Users Engage with Privacy-Protected Wikipedia Data
Harold Triedman, Jayshree Sarathy, Priyanka Nanayakkara +4
In response to calls for open data and growing privacy threats, organizations are increasingly adopting privacy-preserving techniques such as differential privacy (DP) that inject…
Enforcing Demographic Coherence: A Harms Aware Framework for Reasoning about Private Data Release
Mark Bun, Marco Carmosino, Palak Jain +2
The technical literature about data privacy largely consists of two complementary approaches: formal definitions of conditions sufficient for privacy preservation and attacks that…
Models Matter: Setting Accurate Privacy Expectations for Local and Central Differential Privacy
Mary Anne Smart, Priyanka Nanayakkara, Rachel Cummings +2
Differential privacy is a popular privacy-enhancing technology that has been deployed both in industry and government agencies. Unfortunately, existing explanations of differential…
Safer Digital Intimacy For Sex Workers And Beyond: A Technical Research Agenda
Vaughn Hamilton, Gabriel Kaptchuk, Allison McDonald +1
Many people engage in digital intimacy: sex workers, their clients, and people who create and share intimate content recreationally. With this intimacy comes significant security a…
What Are the Chances? Explaining the Epsilon Parameter in Differential Privacy
Priyanka Nanayakkara, Mary Anne Smart, Rachel Cummings +2
Differential privacy (DP) is a mathematical privacy notion increasingly deployed across government and industry. With DP, privacy protections are probabilistic: they are bounded by…
"I need a better description'': An Investigation Into User Expectations For Differential Privacy
Rachel Cummings, Gabriel Kaptchuk, Elissa M. Redmiles
Despite recent widespread deployment of differential privacy, relatively little is known about what users think of differential privacy. In this work, we seek to explore users' pri…
How good is good enough for COVID19 apps? The influence of benefits, accuracy, and privacy on willingness to adopt
Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai +2
A growing number of contact tracing apps are being developed to complement manual contact tracing. A key question is whether users will be willing to adopt these contact tracing ap…