A Study on Cyber Attacks Through Virtual Private Network (VPN) on Financial Institutions

Financial institutions continue to be high-value targets for increasingly sophisticated cyberattacks, with 
adversaries adopting advanced techniques to evade detection and exploit systemic vulnerabilities. Among these 
techniques, the misuse of Virtual Private Networks (VPNs) has emerged as a critical threat vector. VPNs allow 
attackers to conceal their identities, circumvent geo-location filters, and inject malicious traffic into secure 
environments while appearing legitimate (Zhang et al., 2018; ENISA, 2023). This study investigates the 
correlation between VPN-enabled network activity and cyberattack patterns within financial institutions, using a 
comprehensive dataset of 40,000 network traffic records. The dataset comprises 25 variables, including VPN 
flags, anomaly scores, intrusion detection alerts, malware signatures, attack types, user behaviour profiles, and 
device-level metadata. 
A quantitative, descriptive, and analytical research design was employed to examine how VPN-based 
connections influence the frequency, severity, and behavioural characteristics of cyberattacks. Statistical 
techniques and exploratory data analytics were utilized to identify anomalies, risk clusters, and significant 
deviations between VPN and non-VPN traffic. The analysis reveals that VPN-originated traffic exhibits distinctly 
higher anomaly scores, a greater concentration of IDS alerts, and stronger associations with malware-linked 
activities. Attack types such as phishing, brute-force attempts, unauthorized access, and data exfiltration showed 
heightened occurrence through VPN channels, indicating a deliberate strategy by adversaries to leverage the 
anonymity provided by VPN technologies. 
Furthermore, patterns observed in the dataset suggest that compromised or misconfigured VPN 
endpoints pose substantial vulnerabilities within financial networks. The findings emphasize the urgent need for 
financial institutions to strengthen their security frameworks—particularly concerning VPN access controls, 
multi-factor authentication enforcement, behavioral analytics, continuous threat monitoring, and zero-trust 
network models. 
By providing empirical, data-driven evidence of VPN-related risks, this study contributes valuable 
insights into the evolving cyber threat landscape in financial sectors. It highlights the importance of proactive 
defense mechanisms, advanced anomaly detection systems, and policy-level interventions to mitigate the 
growing challenge of VPN-enabled cyberattacks.