A Study on Network Security Architecture and Analysis Using Artificial Neural Network Techniques

Addressing Network Security Challenges Using Artificial Neural Networks

Abstract

The purpose of this research work is to collect and track intrusion events more specifically using the applications of the ANN. The ANN training algorithm utilized to train neural weights is categorized between supervised, unsupervised and recurrent algorithms. Intrusion detection is the practice of observing and monitoring system or network activities for indicators of potential incidents involving the violation of computer security policies. Intrusion Detection could be utilized to protect a host computer or network, and also to be a victim or an assault receiver. The primary goal of this research work will be present a new mixture of an ANN algorithm that would be effective in detecting intrusion in a networked computer setting. This paper provides a vulnerability overview of the IoT and utilizes the ANN to tackle these challenges.