Enhanced Classification of Networks Encrypted Traffic: A Conceptual Analysis of Security Assessments, Implementation, Trends and Future Directions
Year: 2024
Type: article
Abstract: Encryption is a fundamental security measure to safeguard data during transmission to ensure confidentiality while at the same time posing a great challenge for traditional packet and traffic inspection. With the widespread use of encrypted data transport, network traffic encryption is becoming a standard nowadays. This presents a challenge for traffic measurement, especially for analysis and anomaly detection methods, which are dependent on the type of network traffic. In this paper, we survey existing approaches for classification and analysis of encrypted trafficIn response to the proliferation of diverse network traffic patterns from IOT devices, websites, and mobile applications, understanding and classifying encrypted traffic are crucial for network administrators, cybersecurity professionals, and policy enforcement entities. This paper presents a comprehensive exploration of recent advancements in numerous virtual private network and machine-learning-driven encrypted security protocols, that examines their critical role in modern networking and the protection of sensitive data across untrusted networks its traffic analysis and classification. We present the overall procedure and provide a detailed explanation of utilizing machine learning in analyzing and classifying encrypted network traffic. As VPN technologies have evolved over time, and today, they are essential in ensuring secure communications for both personal and enterprise use. This study also delves into various VPN protocols such as PPTP, L2TP/IPsec, OpenVPN, IKEv2/IPsec, and the newer WireGuard, evaluating their security features, strengths, and weaknesses in different network environments and reviewed state-of-the-art techniques and methodologies in traffic analysis. Our aim is to provide insights into current practices and future directions in encrypted traffic analysis and classification, that focusing on the integration of AI for enhanced VPN security and the adaptation of VPN protocols to a post-quantum world especially machine-learning-based analysis.
Authors: Irfan Farooq, Syed Aale Ahmed, Asfar Ali, Muhammad Ali Warraich, Muhammad Aqeel, Hamayun Khan
Institution: Superior University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4406861860