Unveiling Cyber Threats: Exploratory Data Analysis of the Kitsun Network Attack Dataset

The complexity and sophistication of cyber-attacks are constantly evolving, which presents substantial difficulties to the security of networked systems. Researchers and practitioners depend on extensive datasets to study and comprehend new dangers. This study does an exploratory data analysis (EDA) of the Kitsun Network Attack Dataset, to reveal insights into common cyber threats and their features. This type of dataset will, therefore, host a variety of attack types, such as malware infections, denial-of-service assaults, and infiltration attempts, all gathered from various sources. Apply descriptive statistics, visualization methods, and machine learning algorithms to the information provided to carefully analyze it for possible patterns, trends, and anomalies that may indicate possible cyber risks. The results of this study will help give insight into chronological patterns of assaults, typical methods used in attacks, and the efficacy of existing protection systems. We also show how characteristics of attack length and intensity and those of the target's vulnerabilities interact to understand cyber threat environments better. This work therefore brings valuable insights into the domain of cybersecurity with an attempt to explain the rather complex KitSun network attack dataset. The information contained herein will help stakeholders enhance their defensive plans and minimize the impact of cyber-attacks.