Modeling and Predicting Cyber Hacking Breaches

A data breach is a security event, where sensitive data is accessed without any permission from a website or an organization. An information breach will be considered as the purposeful or accidental gathering of secure or personal data from an organization. A breach can be an accession of a data without any permission, these kinds of regulations should be provided with safe and secured framework but this is not happening in many corporations. So, by analyzing the previous attempts (successful or unsuccessful attacks), the proposed model can be trained to adapt to new scenarios and predict the next breach. Further, this research work has designed a model by using machine learning to defend a website from security breaches. The primary aim of this research work is to create a machine learning model, which trains in Realtime and monitors the website or a system and trains from the state-of-art attacks. The proposed model has created a web application using Django, which takes the data from multiple sources such as Amazon, Flipkart, Snapdeal, and Shop clues, which shows the data that is safe to obtain from the website. Then, the data will be sorted on our page and then it will be made secured and illegal for the external people to access the data from our website and the proposed model will monitor the website 24/7. The model is trained daily and it generates predictions from the several of datasets available and from the previous state-of-the-art attacks. This model will be trained from the existing datasets and the history of attacks and breaches on our website.