Machine Learning Based Analysis and Visualization of Cyber Security Attacks on a Company

With the automation of business processes and the growing number of computers used to store sensitive data, the need for secure computer systems becomes more apparent. This necessity becomes much more obvious as systems and applications are spread and accessed across insecure networks like the Internet. Internet usage has become essential for governments, businesses, financial institutions, and millions of ordinary consumers. Analyzing cyber security threats in a corporation using machine learning techniques is the primary objective of this work. This paper introduces analysing some cybersecurity events with different durations and patterns that has been registered using visualization. Making use of machine learning methods like hypothesis testing, Chi-square test, correlation calculations are done on the most targeted IP address, the most logical ports attacked, common type of attacks with durations and patterns are identified using companies’ dataset. This identifies the duration when the company was attacked with attack category, by this common information gathered, the company can shield private data from further malicious attacks.