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Stephanie Garboski

dblp:199/2927 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Privacy and data protection · 87% Usable security · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection
differential privacy
0.312017
Towards Understanding Differential Privacy: When Do People Trust Randomized Response Technique? · CHI 2017
Privacy and data protection › differential privacy › local differential privacy
randomized response
0.312017
Towards Understanding Differential Privacy: When Do People Trust Randomized Response Technique? · CHI 2017
Usable security › usable privacy
privacy decision-making
0.112017
Towards Understanding Differential Privacy: When Do People Trust Randomized Response Technique? · CHI 2017

Methods — techniques the papers use, named apart from their topics

user study · 0.3survey · 0.3
YearPublicationVenuePosition
2017 Towards Understanding Differential Privacy: When Do People Trust Randomized Response Technique?
abstract
As a consequence of living in a data ecosystem, we often relinquish personal information to be used in contexts in which we have no control. In this paper, we begin to examine the usability of differential privacy, a mechanism that proposes to promise privacy with a mathematical "proof" to the data donor. Do people trust this promise and adjust their privacy decisions if the interfaces through which they interact make differential privacy less opaque? In a study with 228 participants, we measured comfort, understanding, and trust using a variant of differential privacy known as Randomized Response Technique (RRT). We found that allowing individuals to see the amount of obfuscation applied to their responses increased their trust in the privacy-protecting mechanism. However, participants who associated obfuscating privacy mechanisms with deception did not make the "safest" privacy decisions, even as they demonstrated an understanding of RRT. We demonstrate that prudent privacy-related decisions can be cultivated with simple explanations of usable privacy.
Brooke Bullek, Stephanie Garboski, Darakhshan J. Mir, Evan M. Peck
CHI2