MetaWatch: Trends, Challenges, and Future of Network Intrusion Detection in the Metaverse

As the Metaverse progresses, its security measures must evolve to safeguard users from cyberattacks. To this end, Artificial Intelligence (AI)-powered Network Intrusion Detection Systems (NIDSs) have been implemented at the network layer to detect and respond to threats in real-time. Our survey -MetaWatch provides a comprehensive overview and analysis of relevant literature, focusing on studies that have explored NIDSs in the Metaverse. Unlike other surveys that have addressed Metaverse security issues more broadly, MetaWatch specifically provides a taxonomy of detection paradigms and defense mechanisms within Metaverse NIDS from 2021 to 2024. Additionally, MetaWatch identifies and discusses the key challenges and problems that impact the development of trustworthy, explainable, scalable, and robust Metaverse NIDS. Overall, the survey provides readers with a concise and informative summary of NIDS issues in the Metaverse and highlights open security problems worth exploring.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-05-09
DOI
https://doi.org/10.1109/jiot.2025.3568477
Citations
8
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
11.88
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article

MetaWatch: Trends, Challenges, and Future of Network Intrusion Detection in the Metaverse

Cosmas Ifeanyi Nwakanma, Judith Nkechinyere Njoku, Ebuka Chinaechetam Nkoro, Jae‐Min Lee et al.
8 citations
IEEE Internet of Things Journal
Advanced Malware Detection Techniques
11.88
article

MetaWatch: Trends, Challenges, and Future of Network Intrusion Detection in the Metaverse

Cosmas Ifeanyi Nwakanma, Judith Nkechinyere Njoku, Ebuka Chinaechetam Nkoro, Jae‐Min Lee, Dong‐Seong Kim
article en
8 citations

Abstract

As the Metaverse progresses, its security measures must evolve to safeguard users from cyberattacks. To this end, Artificial Intelligence (AI)-powered Network Intrusion Detection Systems (NIDSs) have been implemented at the network layer to detect and respond to threats in real-time. Our survey -MetaWatch provides a comprehensive overview and analysis of relevant literature, focusing on studies that have explored NIDSs in the Metaverse. Unlike other surveys that have addressed Metaverse security issues more broadly, MetaWatch specifically provides a taxonomy of detection paradigms and defense mechanisms within Metaverse NIDS from 2021 to 2024. Additionally, MetaWatch identifies and discusses the key challenges and problems that impact the development of trustworthy, explainable, scalable, and robust Metaverse NIDS. Overall, the survey provides readers with a concise and informative summary of NIDS issues in the Metaverse and highlights open security problems worth exploring.

IEEE Internet of Things JournalVol. 12(16)
Kumoh National Institute of Technology (KR), West Virginia University (US)
Climate action
Openalex Percentile: Top 1%
Advanced Malware Detection Techniques
11.88
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MetaWatch: Trends, Challenges, and Future of Network Intrusion Detection in the Metaverse — Cosmas Ifeanyi Nwakanma, Judith Nkechinyere Njoku, et al. · IEEE Internet of Things Journal (2025) | TGRS Research Map | TGRS