Cyber Risk Forecasting Using Data Science Techniques

Abstract

The number of cyber risks is going up and they are getting more complicated as organisations use more digital technologies. These risk factors can affect the data and business operation very severely. This study mainly focusing on data science to predict cyber risks. It can help organisations take a pre-emptive approach to manage cyber security. Most of the cyber security strategies reacts only after a cyber threat occurs, rather than preventing the occurrence. This paper uses data analytical tools and computer models to analyse when and the cyber risks will commence. It looks through the system logs, lists of vulnerabilities of past incidents and information about external threats. The study uses statistics, machine learning and forecasting to make predictions. It also considers what happens when data is missing how to choose the features and how to get the data ready for use. The main goal is to predict cyber risks, like cyber-attacks, cyber-threats and help organisations prepare for them. Cyber risks are a deal and this study is, about cyber risks and how to manage cyber risks using data science techniques.