AuthVR: Securing authentication against shoulder surfing and keystroke inference attacks using virtual reality

bracu.type.groupResearch Publications
datacite.rightsMetadata Only
dc.contributor.authorAli, Md Yeasin
dc.contributor.authorUdoy T.I.
dc.contributor.authorTasin, Md. Ishmam
dc.contributor.authorNahid M.A.
dc.contributor.authorChowdhury F.R.
dc.contributor.authorChowdhury, Farida
dc.contributor.authorFerdous, Md Sadek
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2026-09-13T05:43:19Z
dc.date.available2026-09-13T05:43:19Z
dc.date.issued2025-01-01
dc.description.abstractPasswords serve as the primary authentication mechanism for knowledge-based systems, facilitating user access across a diverse spectrum of applications. Although password-based authentication is commonly employed in high-security environments such as security checkpoints and central control and command systems, it remains susceptible to fraudulent activities, e.g. shoulder-surfing and inference attacks (via direct observation, eavesdropping, or recording) particularly in public or monitored spaces equipped with CCTV cameras. In this paper, we present AuthVR, a Virtual Reality (VR) enabled authentication mechanism creating an additional layer of security in such high-security environments, significantly enhancing existing systems' security. Using Design Science Research Methodology, we assess potential threats and establish the system requirements. We present the architecture, its detailed protocol flow, validate its security through a formal analysis using ProVerif and provide a thorough analysis of the proposal's probable resistance against a number of attack vectors. Additionally, a user study is conducted to evaluate the usability and practical aspects of the system showing a positive impression towards the system.
dc.description.versionPublished
dc.format.extent2087-2096
dc.identifier.citationM. Y. Ali et al., "AuthVR: Securing Authentication Against Shoulder Surfing and Keystroke Inference Attacks using Virtual Reality," 2025 IEEE 24th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Guiyang, China, 2025, pp. 2087-2096, doi: 10.1109/Trustcom66490.2025.00243.
dc.identifier.doi10.1109/Trustcom66490.2025.00243
dc.identifier.issn2324898X
dc.identifier.other2-s2.0-105033616672
dc.identifier.urihttps://hdl.handle.net/10361/29857
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.hasversion10.1109/Trustcom66490.2025.00243
dc.relation.ispartofProceedings of the IEEE International Conference on Trust Security and Privacy in Computing and Communications Trustcom
dc.relation.ispartofseriesProceedings of the IEEE International Conference on Trust Security and Privacy in Computing and Communications Trustcom
dc.relation.urihttps://ieeexplore.ieee.org/document/11354814
dc.subjectAuthentication
dc.subjectKeystroke inference attack
dc.subjectShoulder-surfing
dc.subjectVirtual reality
dc.subjectWeb application security
dc.subject.lcshApplication software--Security measures.
dc.subject.lcshVirtual reality.
dc.titleAuthVR: Securing authentication against shoulder surfing and keystroke inference attacks using virtual reality
dc.typeJournal
oaire.citation.issue2025
person.affiliation.nameBRAC University
person.affiliation.nameShahjalal University of Science and Technology
person.affiliation.nameBRAC University
person.affiliation.nameCryptic Consultancy Limited
person.affiliation.nameCryptic Consultancy Limited
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.identifier.scopus-author-id57842609700
person.identifier.scopus-author-id60529671200
person.identifier.scopus-author-id59345974600
person.identifier.scopus-author-id59328867600
person.identifier.scopus-author-id59328734400
person.identifier.scopus-author-id55490091600
person.identifier.scopus-author-id22034567100

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Demo.jpg
Size:
27.28 KB
Format:
Joint Photographic Experts Group/JPEG File Interchange Format (JFIF)

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: