Demo Data from VLDB 2026 / reviewers in the wild / expert
Chuyang Peng
dblp:416/0719
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0006-9832-8283ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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.
| Network and information security
1 paper |
Privacy and data protection · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection
biometric privacy |
0.9 | 1 | 2025 | Poster: PeekXR: Understanding Privacy Leakages from Eye Gaze in Extended Reality · MobiSys 2025 |
Privacy and data protection › biometric privacy
eye-tracking data privacy |
0.9 | 1 | 2025 | Poster: PeekXR: Understanding Privacy Leakages from Eye Gaze in Extended Reality · MobiSys 2025 |
Immersive interaction
extended reality |
0.3 | 1 | 2025 | Poster: PeekXR: Understanding Privacy Leakages from Eye Gaze in Extended Reality · MobiSys 2025 |
Methods — techniques the papers use, named apart from their topics
gaze sequence classification · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Poster: PeekXR: Understanding Privacy Leakages from Eye Gaze in Extended RealityabstractExtended Reality (XR) headsets are increasingly integrating eye tracking for enhanced user experience, adaptive interfaces, and foveated rendering. However, this rich biometric signal introduces new privacy risks. In this work, we demonstrate that eye-tracking data collected by commercial XR devices can be exploited to infer sensitive user activity. We leverage users' gaze sequences captured while interacting with a VR app to classify the type of content a user is watching. Our results reveal that eye movements alone, without any video or audio context, carry enough information to accurately predict content categories. We discuss the implications of this threat and outline how eye tracking can potentially be used to fingerprint applications and user behavior. This work is a step towards exposing and mitigating emerging privacy threats in immersive systems. Chuyang Peng, Mutahar Ali, Habiba Farrukh |
MobiSys | 1 |