The social metaverse: Battle for privacy
Abstract
Recent advances in technology are rapidly changing the way we interact with the physical world around us. As a result, our digital footprint and digital breadcrumbs are tracked and can reveal not just our identity but also our location, age, shopping preferences, friends, favorite movies, and much more. In the worst case, such tracking may lead to hostile entities coming to know your highly sensitive information such as credit card numbers, social security identity numbers, mother's maiden name, medical history, bank account information, and so on. Social engineering [1] is one of several related ways that this data becomes jeopardized. Furthermore, Internet-connected cameras allow consumers, companies, and government agencies to record animate and inanimate objects in a specific geographic area. Such recordings may be stored in cloud-based storage farms, viewed by humans, or analyzed by machines for various purposes. The information can be gathered and interpreted in multiple ways, such as by surveillance cameras, and can include activity and location inference as well as aggregation and pattern detection.
Integrity signals
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Cites
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Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Researchers are starting to analyse the data and privacy vulnerabilities that will exist in the metaverse.
“Although researchers are starting to analyse the data and privacy vulnerabilities that will exist in the metaverse (Alspach, 2022;Falchuk et al., 2018;Merre, 2022)”
From Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy (2022) · cites this paper as Falchuk et al., 2018
Cites
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“ing [1] is one of several related ways that this data be-”
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Kim, H.-I., Hong, S., & Kim, J. (2005) · Lecture notes in computer science · doi:10.1007/11589990_187 · Cited by 40 · see citing works
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Self-citationJust-in-time reconnaissance and assistance for video game streams and players
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Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., Dennehy, D., Metri, B., Buhalis, D., Cheung, C. M. K., et al. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2022.102542 · Cited by 2,753 · see citing works
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“When it comes to user privacy in the metaverse, three major aspects stand out: personal information, behavior, and communications (Falchuk et al., 2018 ).”
BackgroundUllah, H., Manickam, S., Obaidat, M., Laghari, S. U. A., & Uddin, M. (2023) · IEEE Access · doi:10.1109/access.2023.3286696 · Cited by 198 · see citing works
- Authors
- Falchuk, B., Loeb, S., & Neff, R.
- Affiliations
- InterDigital (United States) (US)
- Venue
- IEEE Technology and Society Magazine
- Published
- 2018-06
- Volume
- 37
- Issue
- 2
- Pages
- 52-61
- ISSN
- 0278-0097 (ISSN-L)
- 1937-416X
- OpenAlex
- W2805804251
- Cited by
- 354
- References
- 9
- Citations by year
- 2026: 25 · 2025: 59 · 2024: 93 · 2023: 118 · 2022: 57 · 2021: 1 · 2017: 1
- FWCI
- 0.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Technology and Society Magazine (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Information Systems › COVID-19 Digital Contact Tracing
- Keywords
- metaverse, privacy, digital footprint, data tracking, social engineering, surveillance cameras, cloud storage, location inference, sensitive data
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