Web-based Intrusion Detection System Using Neural Network

Abstract

As numerous businesses go online, there has been a rise in the use of web-based applications which, therefore, require taking further security. As a result of the large number of users on the internet, people are vulnerable to malicious intruders trying to negotiate the integrity, confidentiality, and availability of resources. The online pattern of a user has to be analyzed to determine if any inconsistency occurs in comparison with the usual pattern. Hence, an Intrusion Detection System is proposed to detect the attacks. The intrusion detection system makes use of an Artificial Neural Network (ANN) which adopts a neural network algorithm. Streamlit was used in the development of the system. For the neural network, rules like; brute force attack, SQL injection, and XSS injection were used to train the model.