Towards Understanding User Privacy Concerns of Internet of Things Sensor Data

Despite the wide adoption of Internet of Things (IoT) devices in people's lives, their privacy implications remain unclear to many users. Privacy policies are used as the major mechanism to deliver this information, and tools are developed to assist users to interpret these policies, there is still a gap between users' perceived privacy and the actual privacy risks they face. Especially for various indirect sensing modalities, where users' comprehension and concerns about their privacy are unknown. We present PrivacyVis, a novel visualization tool that provide an informative and expressive visual representation of the sensors, data processing workflows, and associated privacy risks of IoT devices. Designed to be user-friendly, the tool aims to enhance users' understanding and empower them to make informed decisions about their privacy. PrivacyVis allows us to conduct efficient user surveys to understand user concerns and perceived privacy for IoT devices.

Authors

Institutions

Publication Details

Published
2025-05-06
DOI
https://doi.org/10.1145/3722566.3727627
Primary Topic
Internet Traffic Analysis and Secure E-voting
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards Understanding User Privacy Concerns of Internet of Things Sensor Data

Dipu Ram Roy, Shiwei Fang, Shijia Pan, J. L. Zhao
Internet Traffic Analysis and Secure E-voting
article

Towards Understanding User Privacy Concerns of Internet of Things Sensor Data

Dipu Ram Roy, Shiwei Fang, Shijia Pan, J. L. Zhao
article en

Abstract

Despite the wide adoption of Internet of Things (IoT) devices in people's lives, their privacy implications remain unclear to many users. Privacy policies are used as the major mechanism to deliver this information, and tools are developed to assist users to interpret these policies, there is still a gap between users' perceived privacy and the actual privacy risks they face. Especially for various indirect sensing modalities, where users' comprehension and concerns about their privacy are unknown. We present PrivacyVis, a novel visualization tool that provide an informative and expressive visual representation of the sensors, data processing workflows, and associated privacy risks of IoT devices. Designed to be user-friendly, the tool aims to enhance users' understanding and empower them to make informed decisions about their privacy. PrivacyVis allows us to conduct efficient user surveys to understand user concerns and perceived privacy for IoT devices.

University of California, Merced (US), Bangladesh University of Engineering and Technology (BD), Augusta University (US)
Openalex Percentile: Top 96%
Internet Traffic Analysis and Secure E-voting
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Towards Understanding User Privacy Concerns of Internet of Things Sensor Data — Dipu Ram Roy, Shiwei Fang, et al. · (2025) | TGRS Research Map | TGRS