Progression of the Protection Networking System Depending on International Virtual Private Network.

Hameed, Basilar H.; Saleh, Zina A.

The increasing number of network users and the development of networks in modern times have raised concerns regarding the security of networks. The current emphasis on network security pertains to web-based networks, as they enable individuals from diverse locations to access them via the Internet, thereby raising security concerns. To address these challenges, various technologies have been developed to ensure the security of networks and compliance with privacy regulations. This paper proposes incorporating a Virtual Private Network (VPN) as a crucial component for protecting network integrity, contingent upon achieving specified network performance indicators, such as throughput and latency. The VPN ensures data security and prevents unauthorized external access by establishing encrypted tunnels over network connections. Moreover, to increase the security of the VPN connections, a deep learning algorithm known as an Artificial Neural Network (ANN) is used during the training phase to analyze the patterns of potential network attacks to predict future network attacks. The outcomes of this implementation exhibit noteworthy performance, as the AI attack predictor attains an exceptional accuracy rate of up to 98%. The superior accuracy of the ANN-based algorithm makes it the top performer among the evaluated algorithms, providing a dependable and effective method for enhancing network security. The current comparative analysis emphasizes the superiority of the ANN-based strategy and its capacity to address security concerns effectively.

VIRTUAL private networks; MACHINE learning; COMPUTER network security; DEEP learning; INTERNET access; INTERNET privacy; DATA privacy

International Journal of Safety & Security Engineering, 2023, Vol 13, Issue 5, p863

2041-9031

Academic Journal

10.18280/ijsse.130510