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Sarah Pearman

dblp:183/8079 · also Sarah K. Pearman · DBLP profile ↗
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8ranked-venue papers
2as first author
2since 2021 · last 2022
0000-0003-0038-5521ORCID · corroborated

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

Human-computer interaction and ubiquitous computing · 6 · 1 since 2021Security and privacy · 4 · 2 first-author · 1 since 2021

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
3 papers
Authentication and access control · 67% Cyber-physical and IoT security · 25% Privacy and data protection · 8%
Human-computer interaction and pervasive computing
3 papers
Collaborative and social computing · 57% Usability and user experience research · 33% Ubiquitous computing and smart environments · 10%

Topics — the 10 heaviest of 12, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cyber-physical and IoT security
iot privacy
0.412020
Informing the Design of a Personalized Privacy Assistant for the Internet of Things · CHI 2020
Collaborative and social computing › information sharing
content sharing
0.312017
Exploring Topic-Based Sharing Mechanisms · CHI 2017
Collaborative and social computing
social media
0.312017
Exploring Topic-Based Sharing Mechanisms · CHI 2017
Authentication and access control › password security
password behavior
0.312017
Let's Go in for a Closer Look: Observing Passwords in Their Natural Habitat · CCS 2017
Authentication and access control › password security › password management
password managers
0.312017
Let's Go in for a Closer Look: Observing Passwords in Their Natural Habitat · CCS 2017
Authentication and access control › password security
password reuse
0.312017
Let's Go in for a Closer Look: Observing Passwords in Their Natural Habitat · CCS 2017
Authentication and access control
password security
0.312017
Let's Go in for a Closer Look: Observing Passwords in Their Natural Habitat · CCS 2017
Ubiquitous computing and smart environments
internet of things
0.112020
Informing the Design of a Personalized Privacy Assistant for the Internet of Things · CHI 2020
Collaborative and social computing › social media
audience management
0.112017
Exploring Topic-Based Sharing Mechanisms · CHI 2017
Collaborative and social computing › computer-mediated communication
selective sharing
0.112017
Exploring Topic-Based Sharing Mechanisms · CHI 2017

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

user study · 0.9semi-structured interviews · 0.9interview study · 0.3field study · 0.3diary study · 0.3design probe · 0.3
YearPublicationVenuePosition
2022 Identifying User Needs for Advertising Controls on Facebook
abstract
We conducted an online survey and remote usability study to explore user needs related to advertising controls on Facebook and determine how well existing controls align with these needs. Our survey results highlight a range of user objectives related to controlling Facebook ads, including being able to select what ad topics are shown or what personal information is used in ad targeting. Some objectives are achievable with Facebook's existing controls, but participants seemed to be unaware of them, suggesting issues of discoverability. In our remote usability study, participants noted areas in which the usability of Facebook's advertising controls could be improved, including the location, layout, and explanation of controls. Additionally, we found that users could be categorized into four groups based on their privacy concerns related to Facebook's data collection practices, objectives for controlling their ad experience, and willingness to engage with advertising controls. Our findings provide a set of user requirements for advertising controls, applicable to Facebook as well as other platforms, that would better align such controls with users' needs and expectations.
Hana Habib, Sarah Pearman, Ellie Young, Ishika Saxena, Lorrie Faith Cranor
Proc. ACM Hum. Comput. Interact.2
2022 User-friendly yet rarely read: A case study on the redesign of an online HIPAA authorization
abstract
In this paper we describe the iterative evaluation and refinement of a consent flow for a chatbot being developed by a large U.S. health insurance company. This chatbot’s use of a cloud service provider triggers a requirement for users to agree to a HIPAA authorization. We highlight remote usability study and online survey findings indicating that simplifying the interface and language of the consent flow can improve the user experience and help users who read the content understand how their data may be used. However, we observe that most users in our studies, even those using our improved consent flows, missed important information in the authorization until we asked them to review it again. We also show that many people are overconfident about the privacy and security of healthcare data and that many people believe HIPAA protects in far more contexts than it actually does. Given that our redesigns following best practices did not produce many meaningful improvements in informed consent, we argue for the need for research on alternate approaches to health data disclosures such as standardized disclosures; methods borrowed from clinical research contexts such as multimedia formats, quizzes, and conversational approaches; and automated privacy assistants.
Sarah Pearman, Ellie Young, Lorrie Faith Cranor
Proc. Priv. Enhancing Technol.1
2020 Informing the Design of a Personalized Privacy Assistant for the Internet of Things
abstract
Internet of Things (IoT) devices create new ways through which personal data is collected and processed by service providers. Frequently, end users have little awareness of, and even less control over, these devices' data collection. IoT Personalized Privacy Assistants (PPAs) can help overcome this issue by helping users discover and, when available, control the data collection practices of nearby IoT resources. We use semi-structured interviews with 17 participants to explore user perceptions of three increasingly more autonomous potential implementations of PPAs, identifying benefits and issues associated with each implementation. We find that participants weigh the desire for control against the fear of cognitive overload. We recommend solutions that address users' differing automation preferences and reduce notification overload. We discuss open issues related to opting out from public data collections, automated consent, the phenomenon of user resignation, and designing PPAs with at-risk communities in mind.
Jessica Colnago, Yuanyuan Feng, Tharangini Palanivel, Sarah Pearman, Megan Ung, Alessandro Acquisti, Lorrie Faith Cranor, Norman M. Sadeh
CHI4
2020 "It's a scavenger hunt": Usability of Websites' Opt-Out and Data Deletion Choices
abstract
We conducted an in-lab user study with 24 participants to explore the usefulness and usability of privacy choices offered by websites. Participants were asked to find and use choices related to email marketing, targeted advertising, or data deletion on a set of nine websites that differed in terms of where and how these choices were presented. They struggled with several aspects of the interaction, such as selecting the correct page from a site's navigation menu and understanding what information to include in written opt-out requests. Participants found mechanisms located in account settings pages easier to use than options contained in privacy policies, but many still consulted help pages or sent email to request assistance. Our findings indicate that, despite their prevalence, privacy choices like those examined in this study are difficult for consumers to exercise in practice. We provide design and policy recommendations for making these website opt-out and deletion choices more useful and usable for consumers.
Hana Habib, Sarah Pearman, Yixin Zou, Alessandro Acquisti, Lorrie Faith Cranor, Norman M. Sadeh, Florian Schaub
CHI2
2017 Let's Go in for a Closer Look: Observing Passwords in Their Natural Habitat
abstract
Text passwords---a frequent vector for account compromise, yet still ubiquitous---have been studied for decades by researchers attempting to determine how to coerce users to create passwords that are hard for attackers to guess but still easy for users to type and memorize. Most studies examine one password or a small number of passwords per user, and studies often rely on passwords created solely for the purpose of the study or on passwords protecting low-value accounts. These limitations severely constrain our understanding of password security in practice, including the extent and nature of password reuse, password behaviors specific to categories of accounts (e.g., financial websites), and the effect of password managers and other privacy tools.
Sarah Pearman, Jeremy Thomas, Pardis Emami Naeini, Hana Habib, Lujo Bauer, Nicolas Christin, Lorrie Faith Cranor, Serge Egelman, Alain Forget
CCS1
2017 Exploring Topic-Based Sharing Mechanisms
abstract
General-purpose content-sharing platforms make it difficult for users to limit sharing to people interested in particular topics. Additional topic-based controls may allow users to better reach desired audiences. Designing such tools requires understanding current interest-based targeting techniques and the potential impact of additional mechanisms. We present an exploratory, interview-based study (n = 16) that addresses these dynamics for Facebook. We use diary-driven probes to explore general topic-based sharing across applications. We then use Facebook-based mockups to probe use cases and design tensions around adding topic-based sharing mechanisms to Facebook. We find that participants currently draw on various audience-limiting and reaching strategies to target interest-based audiences. Participants felt additional topic-based sharing mechanisms on Facebook might allow them to avoid oversharing or offending others and allow them to target improved audiences or share improved content. Usable topic-based sharing tools would also need to account, however, for participants' varied desired engagement strategies.
Manya Sleeper, Lorrie Faith Cranor, Sarah Pearman
CHI3
2017 Replication: Challenges in Using Data Logs to Validate Phishing Detection Ability Metrics
Casey Inez Canfield, Baruch Fischhoff, Alain Forget, Sarah Pearman, Jeremy Thomas
SOUPS5
2016 Do or Do Not, There Is No Try: User Engagement May Not Improve Security Outcomes
Alain Forget, Sarah Pearman, Jeremy Thomas, Alessandro Acquisti, Nicolas Christin, Lorrie Faith Cranor, Serge Egelman, Marian Harbach, Rahul Telang
SOUPS2