An Artificial Intelligent (AI) Automated Compliance Framework for Securing Critical Infrastructure

This project is named as an AI-Based Automated Compliance Framework to protect critical infrastructure. This project aims to offer an automated mechanism of securing critical infrastructure using machine learning/ Artificial Intelligence based tool offering a timely and accurate compliance mechanism (initiated by the detected network attacks activity) and predictive models. These predictive models will be machine learning algorithms (Random Forest, Support Vector Regrition, Logistic Regression, etc.) that will be utilized to process network traffic data to predict identified active network threats, like CROSS-SITE SCRIPING (XSS), Distributed Denial of Service (DDoS), Man-in-the-Middle (MITM), Structured Query Language (SQL Injection) etc. To enable users to use the framework and submit their network traffic data, use and visualize compliance suggestions according to the security framework, an artificial intelligent User Interface (Flask/MySQL/joblib) was created. The end product of this project is to come up with an automated compliance/security process which will enable timely and appropriate detection, analysis as well as the response to emerging security threat to critical infrastructure.