Detection of Cyberattacks on the Metaverse Based on First-Order Logic

Authors: Sulaiman Al Amro

Abstract:

There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies, and therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and thus the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.

Keywords: Cyberattacks, detection, first-order logic, Metaverse, privacy, security.

References:

[1] K. Yang, Z. Zhang, Y. Tian. and J. Ma. “A secure authentication framework to guarantee the traceability of avatars in Metaverse.” IEEE Transactions on Information Forensics and Security. 2023.
[2] N. A. Dahan, M. Al-Razgan, A. Al-Laith, M. A. Alsoufi, M. S. Al-Asaly, and T. Alfakih, “Metaverse framework: A case study on E-learning environment (ELEM).” Electronics, 11(10), p.1616. 2022
[3] R. Di Pietro and S. Cresci. “Metaverse: security and privacy issues.” In 2021 Third IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) (pp. 281-288). Dec 2021
[4] U. Kose. “Security Issues in Artificial Intelligence Use for Metaverse and Digital Twin Setups”. In: E. Karaarslan, Ö. Aydin, Ü Cali, M. Challenger, (eds) Digital Twin Driven Intelligent Systems and Emerging Metaverse. Springer, Singapore. https://doi.org/10.1007/978-981-99-0252-1_17 2023.
[5] Unity Technologies, https://learn.unity.com/tutorial/configuring-an-xr-rig-with-the-xr-interaction-toolkit. Accessed 03/08/2023.
[6] S. Al Amro, and A. Cau. “Behaviour-based virus detection system using Interval Temporal Logic.” In 2011 6th International Conference on Risks and Security of Internet and Systems (CRiSIS) (pp. 1-6). IEEE. Sept 2011.
[7] B. Bütün, A. T. J. Akem, M. Gucciardo, and M. Fiore. “Fast Detection of Cyberattacks on the Metaverse through User-plane Inference.” In International Conference on Metaverse Computing, Networking and Applications. June 2023.
[8] T. Gaber, J. B. Awotunde, M. Torky, S. A. Ajagbe, M. Hammoudeh and W. Li. Metaverse -IDS: “Deep learning-based intrusion detection system for Metaverse -IoT networks.” Internet of Things, 24, p.100977. 2023.
[9] K. Y. Lam, L. Yang, A. Alhilal, L. H. Lee, G. Tyson, and P. Hui, P. Human-avatar interaction in Metaverse: Framework for full-body interaction. In Proceedings of the 4th ACM International Conference on Multimedia in Asia (pp. 1-7). Dec 2022.
[10] E. A. Tuli, A. Zainudin, M. J. A. Shanto, J. M. Lee, and D. S. Kim. “MediaPipe-based Real-time Interactive Avatar Generation for Metaverse.” InProc. Korea Commun. Soc. Conf., pp.1370-1371. 2023.
[11] J. Y. Halpern and B. C. Moszkowski. “Executing temporal logic programs”. Cambridge University Press, Cambridge etc. 1986, xiii+ 125 pp. Journal of Symbolic Logic, 53(1). 1988.