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Fengliang He

dblp:239/9995 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2025
0009-0005-1248-1539ORCID · corroborated

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

Software engineering, systems software and programming languages · 2 · 2 since 2021Security and privacy · 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
2 papers
Privacy and data protection · 54% Web and mobile security · 25% Systems and software security · 22%
Software engineering, system software, and programming languages
1 paper
Program analysis · 100%
Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection › privacy policy
privacy policy analysis
1.022025
An Empirical Study on Oculus Virtual Reality Applications: Security and Privacy Perspectives · ICSE 2024
An Empirical Study on Meta Virtual Reality Applications: Security and Privacy Perspectives · IEEE Trans. Software Eng. 2025
Web and mobile security
mobile application security
0.912025
An Empirical Study on Meta Virtual Reality Applications: Security and Privacy Perspectives · IEEE Trans. Software Eng. 2025
Privacy and data protection › information leakage
privacy leakage
0.912025
An Empirical Study on Meta Virtual Reality Applications: Security and Privacy Perspectives · IEEE Trans. Software Eng. 2025
Program analysis
static analysis
0.312025
An Empirical Study on Meta Virtual Reality Applications: Security and Privacy Perspectives · IEEE Trans. Software Eng. 2025
Program analysis › static analysis
taint analysis
0.312025
An Empirical Study on Meta Virtual Reality Applications: Security and Privacy Perspectives · IEEE Trans. Software Eng. 2025
Virtual and augmented reality › virtual reality
virtual reality applications
0.212024
An Empirical Study on Oculus Virtual Reality Applications: Security and Privacy Perspectives · ICSE 2024

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

taint analysis · 3.3static analysis · 3.3privacy policy analysis · 2.5user review analysis · 1.7privacy-policy analysis · 0.8
YearPublicationVenuePosition
2025 AcouListener: An Inaudible Acoustic Side-Channel Attack on AR/VR Systems
Fengliang He, Hongning Dai, Hanyang Guo, Xiapu Luo, Jiadi Yu
ESORICS (3)1
2025 An Empirical Study on Meta Virtual Reality Applications: Security and Privacy Perspectives
abstract
Virtual Reality (VR) has accelerated its prevalent adoption in emerging metaverse applications, but it is not a fundamentally new technology. On the one hand, most VR operating systems (OS) are based on off-the-shelf mobile OS (e.g., Android OS). As a result, VR apps also inevitably inherit privacy and security deficiencies from conventional mobile apps. On the other hand, in contrast to traditional mobile apps, VR apps can achieve an immersive experience via diverse VR devices, such as head-mounted displays, body sensors, and controllers. However, achieving this requires the extensive collection of privacy-sensitive human biometrics (e.g., hand-tracking and face-tracking data). Moreover, VR apps have been typically implemented by 3D gaming engines (e.g., Unity), which also contain intrinsic security vulnerabilities. Inappropriate use of these technologies may incur privacy leaks and security vulnerabilities although these issues have not received significant attention compared to the proliferation of diverse VR apps. In this paper, we develop a security and privacy assessment tool, namely the VR-SP detector for VR apps. The VR-SP detector has integrated program static analysis tools and privacy-policy analysis methods. Using the VR-SP detector, we conduct a comprehensive empirical study on 900 popular VR apps. We obtain the original apps from the popular SideQuest app store and extract Android PacKage (APK) files via the Meta Quest 2 device. We evaluate the security vulnerabilities and privacy data leaks of these VR apps through VR app analysis, taint analysis, privacy policy analysis, and user review analysis. We find that a number of security vulnerabilities and privacy leaks widely exist in VR apps. Moreover, our results also reveal conflicting representations in the privacy policies of these apps and inconsistencies of the actual data collection with the privacy-policy statements of the apps. Further, user reviews also indicate their privacy concerns about relevant biometric data. Based on these findings, we make suggestions for the future development of VR apps.
Hanyang Guo, Hongning Dai, Xiapu Luo, Gengyang Xu, Fengliang He, Zibin Zheng
IEEE Trans. Software Eng.5
2024 An Empirical Study on Oculus Virtual Reality Applications: Security and Privacy Perspectives
abstract
Although Virtual Reality (VR) has accelerated its prevalent adoption in emerging metaverse applications, it is not a fundamentally new technology. On one hand, most VR operating systems (OS) are based on off-the-shelf mobile OS (e.g., Android). As a result, VR apps also inherit privacy and security deficiencies from conventional mobile apps. On the other hand, in contrast to conventional mobile apps, VR apps can achieve immersive experience via diverse VR devices, such as head-mounted displays, body sensors, and controllers though achieving this requires the extensive collection of privacy-sensitive human biometrics (e.g., hand-tracking and face-tracking data). Moreover, VR apps have been typically implemented by 3D gaming engines (e.g., Unity), which also contain intrinsic security vulnerabilities. Inappropriate use of these technologies may incur privacy leaks and security vulnerabilities although these issues have not received significant attention compared to the proliferation of diverse VR apps. In this paper, we develop a security and privacy assessment tool, namely the VR-SP detector for VR apps. The VR-SP detector has integrated program static analysis tools and privacy-policy analysis methods. Using the VR-SP detector, we conduct a comprehensive empirical study on 500 popular VR apps. We obtain the original apps from the popular Oculus and SideQuest app stores and extract APK files via the Meta Oculus Quest 2 device. We evaluate security vulnerabilities and privacy data leaks of these VR apps by VR app analysis, taint analysis, and privacy-policy analysis. We find that a number of security vulnerabilities and privacy leaks widely exist in VR apps. Moreover, our results also reveal conflicting representations in the privacy policies of these apps and inconsistencies of the actual data collection with the privacy-policy statements of the apps. Based on these findings, we make suggestions for the future development of VR apps.
Hanyang Guo, Hongning Dai, Xiapu Luo, Zibin Zheng, Gengyang Xu, Fengliang He
ICSE6