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Open Access

ARTICLE

Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

Saad Abdalla Agaili Mohamed*, Sefer Kurnaz
Department of Electrical and Computer Engineering, Altinbas University, Istanbul, 34000, Turkey
* Corresponding Author: Saad Abdalla Agaili Mohamed. Email: email
(This article belongs to the Special Issue: Applying AI Techniques for Cyber Physical Systems and Security Solutions: From Research to Practice)

Computers, Materials & Continua https://doi.org/10.32604/cmc.2024.050474

Received 07 February 2024; Accepted 20 May 2024; Published online 19 June 2024

Abstract

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world. However, increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorize VPN network data. We present a novel VPN network traffic flow classification method utilizing Artificial Neural Networks (ANN). This paper aims to provide a reliable system that can identify a virtual private network (VPN) traffic from intrusion attempts, data exfiltration, and denial-of-service assaults. We compile a broad dataset of labeled VPN traffic flows from various apps and usage patterns. Next, we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous actions. To effectively process and categorize encrypted packets, the neural network model has input, hidden, and output layers. We use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral properties. We also use cutting-edge optimization methods to optimize network characteristics and performance. The suggested ANN-based categorization method is extensively tested and analyzed. Results show the model effectively classifies VPN traffic types. We also show that our ANN-based technique outperforms other approaches in precision, recall, and F1-score with 98.79% accuracy. This study improves VPN security and protects against new cyberthreats. Classifying VPN traffic flows effectively helps enterprises protect sensitive data, maintain network integrity, and respond quickly to security problems. This study advances network security and lays the groundwork for ANN-based cybersecurity solutions.

Keywords

VPN; network traffic flow; ANN; classification; intrusion detection; data exfiltration; encrypted traffic; feature extraction; network security

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