Electric Network Frequency as Environmental Fingerprint for Metaverse Security: A Comprehensive Survey
Year: 2025
Type: article
Abstract: The rapid expansion of the Metaverse presents complex security challenges, particularly in verifying virtual objects and avatars within immersive environments. Conventional authentication methods, such as passwords and biometrics, often prove inadequate in these dynamic environments, especially as essential infrastructures, such as smart grids, integrate with virtual platforms. Cybersecurity threats intensify as advanced attacks introduce fraudulent data, compromising system reliability and safety. Using electric network frequency (ENF)-a naturally varying signal emitted from power grids-provides an innovative environmental fingerprint to authenticate digital twins and metaverse entities in the smart grid. This paper introduces an advanced framework that employs ENF for realtime authentication, leveraging its proven effectiveness in audioforensic analysis and grid stability monitoring. By capturing ENF as a unique signature with a time-stamped signature, this method strengthens security by directly correlating physical grid behavior and virtual interactions, effectively combating threats such as deep-fake manipulations. Building upon recent developments in signal processing, this strategy reinforces the integrity of digital environments, delivering robust protection against evolving cyber-physical risks and facilitating secure, scalable virtual infrastructures.
Source: Computers
Authors: Mohsen Hatami, Lhamo Dorje, Xiaohua Li, Yu Chen
Institution: Binghamton University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,172
OpenAlex ID: W4413250403