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Eimaan Saqib

dblp:345/2238 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0001-8467-6670ORCID · reported

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

Human-computer interaction and ubiquitous computing · 1 · 1 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.

Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 100%
Network and information security
1 paper
Privacy and data protection · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Ubiquitous computing and smart environments › smart home
smart home privacy
0.912025
Bystander Privacy in Smart Homes: A Systematic Review of Concerns and Solutions · ACM Trans. Comput. Hum. Interact. 2025
Privacy and data protection › image privacy
bystander privacy
0.312025
Bystander Privacy in Smart Homes: A Systematic Review of Concerns and Solutions · ACM Trans. Comput. Hum. Interact. 2025

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

systematic review · 1.7
YearPublicationVenuePosition
2025 Bystander Privacy in Smart Homes: A Systematic Review of Concerns and Solutions
abstract
Smart home devices, such as security cameras and voice assistants, have seen widespread adoption due to the utility and convenience they offer to users. The deployment of these devices in homes, however, raises privacy concerns for bystanders—people who may not necessarily have a say in the deployment and configuration of these devices, and yet are exposed to or affected by their data collection. Examples of bystanders include guests, short-term tenants, and domestic workers. Prior work has studied the privacy concerns of different bystander groups and proposed design solutions for addressing these concerns. In this article, we present a systematic review of previous studies, describing how smart home bystanders are defined and classified, and illuminating the range of concerns and solutions proposed in the existing academic literature. We also discuss limitations in prior work, barriers to the uptake of research-based solutions by industry, and identify avenues for future research.
Eimaan Saqib, Shijing He, Junghyun Choy, Ruba Abu-Salma, Jose M. Such, Julia Bernd, Mobin Javed
ACM Trans. Comput. Hum. Interact.1