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.
Authors
- Cosmas Ifeanyi Nwakanma (ORCID: https://orcid.org/0000-0003-3614-2687)
- Judith Nkechinyere Njoku (ORCID: https://orcid.org/0000-0002-2294-9204)
- Ebuka Chinaechetam Nkoro (ORCID: https://orcid.org/0000-0001-6958-4073)
- Jae‐Min Lee (ORCID: https://orcid.org/0000-0001-6885-5185)
- Dong‐Seong Kim (ORCID: https://orcid.org/0000-0002-2977-5964)
Institutions
- Kumoh National Institute of Technology (KR)
- West Virginia University (US)
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