AI-Driven VPN Threat Detection and Preventive Mechanism
DOI:
https://doi.org/10.63530/IJCSITR_2026_07_01_002Keywords:
MITM Attack, VPN, ARP Spoofing, Signature-Based Detection, Network SecurityAbstract
The widespread adoption of remote work has significantly established the Virtual Private Networks (VPNs) as a critical security tool since data remains vulnerable to Man-in-theMiddle (MITM) attacks at the local network layer. Hence, the data is being intercepted and manipulated by adversaries before it enters the secure tunnel. However, this research addresses this vulnerability by designing, implementing, and evaluating a real-time hybrid detection and prevention system for MITM attacks on VPN connections. Similarly, a controlled laboratory environment was used to simulate ARP spoofingbased MITM attacks against a commercial VPN client. Thus, the network traffic was analyzed to identify distinctive signatures of interception and integrated into a Python-based detection engine using Scapy. The signature-based and rule-based techniques were combined to monitor ARP traffic for inconsistencies such as IP-MAC binding violations and Unsolicited ARP replies. Interestingly, a 98.7% detection rate was achieved with an average response latency of 340 milliseconds. An automated mitigation module successfully neutralized 96.8% of attacks by broadcasting corrective ARP packets to restore legitimate network mappings.
References
Coro, M. B. (2024). Information security in remote work: Strategies and challenges in a post-pandemic world. Revista Sistemática, 14(4), 995–999. https://doi.org/10.56238/rcsv14n4-020
Deepika, C., & Abirami, Dr. K. (2024). Current Scenario About Virtual Private Network (Vpn) Cyber Security Threats. Futuristic Trends in Artificial Intelligence Volume 3 Book 11, 3, 101–112. https://doi.org/10.58532/v3bkai11p4ch3
Elmaghraby, R. T., Abdel Aziem, N. M., Sobh, M. A., & Bahaa-Eldin, A. M. (2024). Encrypted network traffic classification based on machine learning. Ain Shams Engineering Journal, 15(2), 102361. https://doi.org/10.1016/j.asej.2023.102361
Gentile, A. F., Macrì, D., Greco, E., & Fazio, P. (2024). Overlay and Virtual Private Networks Security Performances Analysis with Open Source Infrastructure Deployment. Future Internet, 16(8), 1–25. https://doi.org/10.3390/fi16080283
Guerra-Manzanares, A., Caprolu, M., & Di Pietro, R. (2025). A comprehensive review on machine learning-based VPN detection: Scenarios, methods, and open challenges. Computer Science Review, 58(June), 100781. https://doi.org/10.1016/j.cosrev.2025.100781
Hasan, M., & Malik, T. (2024a). AI-Enhanced VPN Security Framework: Integrating Open-Source Threat Intelligence and Machine Learning to Secure Digital Networks. European Conference on Information Warfare and Security, ECCWS, 764–772. https://doi.org/10.34190/eccws.23.1.2505
Hasan, M., & Malik, T. (2024b). AI-Enhanced VPN Security Framework: Integrating Open-Source Threat Intelligence and Machine Learning to Secure Digital Networks. European Conference on Information Warfare and Security, ECCWS, 764–772. https://doi.org/10.34190/eccws.23.1.2505
Jain, V. K., Aggrawal, J., Dangi, R., Prasad Shukla, S. S., Yadav, A. K., & Choudhary, G. (2025). Unmasking the True Identity: Unveiling the Secrets of Virtual Private Networks and Proxies. Information (Switzerland), 16(2), 1–18. https://doi.org/10.3390/info16020126 [9] Kumar, R. R. (2024). Security for Cloud D ata Protecting by VPN. 13(5).
Michael Oladipo Akinsanya, Cynthia Chizoba Ekechi, & Chukwuekem David Okeke. (2024). Virtual Private Networks (Vpn): a Conceptual Review of Security Protocols and Their Application in Modern Networks. Engineering Science & Technology Journal, 5(4), 1452–1472. https://doi.org/10.51594/estj.v5i4.1076
Nair, S. S., & Lakshmikanthan, G. (2020). Beyond VPNs: Advanced Security Strategies for the Remote Work Revolution. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 03(05), 1283–1294. https://doi.org/10.15680/ijmrset.2020.0305009
Ponnuru, S. P. (2024). Advanced Network Security: Evaluating Firewall and Vpn Strategies for Robust Protection in Modern Telecommunications. International Journal of Research In Computer Applications and Information Technology (IJRCAIT), 7(2), 1359.
Putra, S., Iqbal, M., Putera, A., & Siahaan, U. (2024). Network Security Design Using Virtual Private Network (VPN) Method By Utilizing Point To Point Tunneling Protocol (PPTP) Technology On Local Area Network (LAN). International Journal of Computer Sciences and Mathematics Engineering Journal Homepage: Www.Ijecom.Org International Journal of Computer Sciences and Mathematics Engineering Journal Homepage. www.ijecom.org
Qollakaj, K., Larsson, L. E., & Memeti, S. (2025). Cybersecurity of remote work migration: A study on the VPN security landscape post Covid-19 outbreak. Array, 27(September 2024), 100437. https://doi.org/10.1016/j.array.2025.100437
Razooqi, Y. S., & Pekar, A. (2025). VPN Traffic Analysis: A Survey on Detection and Application Identification. IEEE Access, 13(June), 132830–132848. https://doi.org/10.1109/ACCESS.2025.3592152
Scott, V. A. B., & Giancarlo, S. A. (2024). Designing the VPN with Top-Down to Improve Information Security. International Journal of Advanced Computer Science and Applications, 15(6), 182–190. https://doi.org/10.14569/IJACSA.2024.0150620
Shingloo, H., Mishra, S., Zambare, H., Jaiswal, A., & Kumar, M. (2024). Designing A VPN Using Open Network Infrastructure with Enhanced Security and Performance. 11(7), 40–46.
Sun, Y., Wang, B., Wang, C., & Wei, Y. (2021). On Man-in-the-Middle Attack Risks of the VPN Gate Relay System. Security and Communication Networks, 2021. https://doi.org/10.1155/2021/9091675
Tuyisabe, R., Ngugi, Dr. J., & Sumbiri, Dr. D. (2025). Leveraging Site-to-Site VPN and BGP Protocols to Enhance Digital Resource Sharing Among TVET Institutions in Rwanda. Journal of Information and Technology, 5(8), 36–46. https://doi.org/10.70619/vol5iss8pp36-46
Zohaib, S. M., Sajjad, S. M., Iqbal, Z., Yousaf, M., Haseeb, M., & Muhammad, Z. (2024). Zero Trust VPN (ZT-VPN): A Systematic Literature Review and Cybersecurity Framework for Hybrid and Remote Work. Information (Switzerland), 15(11), 1–25. https://doi.org/10.3390/info15110734
Zscaler ThreatLabz team. (2024). Zscaler ThreatLabz 2024 Phishing Report. https://www.zscaler.com/resources/industry-reports/threatlabz-phishing-report-2024.pdf
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Amaka Eugenia Ngozi, Okpalla Chidimma Lilian, Ezea Jonathan Ikechukwu, Ibeneme-Sabinus Ifeoma Livina, Nworuh Godwinner Emeka, Atomatofa Emmanuel Oghenero, Gloria Ngozi Ezeh, Ugbor Ihechiluru Chinwe, A.A. Galadima (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
