Enhancing VPN Security: A Comparative Study of LSTM and GRU Models

Abstract

This chapter presents a comprehensive assessment of VPN (Virtual Private Network) security using different deep learning algorithms. The purpose of the study is to predict whether a given VPN IP address is safe to use by detecting IP address leaks, DNS leaks, encryption strength, and anomalies in VPN behavior. We use machine deep learning algorithms like Long Short Memory (LSTM), Gated Recurrent Units (GRU), to address these critical aspects. The performance of these algorithms is comprehensively compared using evaluation metrics such as Accuracy percentage, Mean Squared Error (MSE), R-Squared(R^2) etc. The results provide valuable information for choosing the most effective technology to ensure the security and privacy of VPN connections.