Abstract
One of the main domains in security is cybersecurity. With the increasing usage of the internet daily, network and computing have become an important target for hackers.Most of them are unpredictable. These attacks can have a huge impact on the organization or country. There has to be some solution to detect these attacks before their occurrence. Nowadays data visualization is being used in every place where we can improve, measure,and control. The scenario described in the challenge is a fabricated one, but hacking and cyber crimes are practical issues that are seen around us daily. The challenge utilizes the data from one of the ethical hacking organizations. The sole purpose is to find the solution to a cyber event that affected the world by implementing visual analytics from the dataset given by the VAST challenge. The main aim here is to exhibit the significance of data analysis and visualization for resolving an issue that has been given in the VAST challenge. According to the challenge specified in IEEE VAST 2020 as a result of continuous cyber attacks, certain white-hat hacker organizations decided to protect the internet. As the intensity of the attacks increased, one of the organizations by mistake launched a cyber event that bought down the entire internet. None of them can analyze the reasons why it happened and wants to get in touch with the group so that the effect can be neutralized. The solution can be obtained from the data available from the center for global cyber strategy(CGCS). For my project, I created an interactive visualization that would help us detect the group that closely matches with the group that launched the cyber attack. With the help of visualization, I have identified the group pattern that will completely or partially match the hacker group using tools like Trifacta, Observable, d3.js, Javascript, HTML, CSS. Thus, with the help of visualization, not only experts but also beginners can easily understand and analyze the potential of cybersecurity attacks The visualizations usually help a better understanding of the reasons why there has been an attack and the location of the malicious activity. In this project, we will be looking at the fictitious dataset from CGCS to analyze and display the necessity of visualization tools while solving real-time problems.