Global Cancer Data Analysis

In this project, I analyzed global cybersecurity data to understand global trends in AI, and their insights help identify and address the most significant vulnerabilities in AI.

The analysis included:

Categorization of new types (malware, phishing, ransomware, DDoS attacks, etc.)

Analysis of the most targeted countries

Reading for a year or more

Identification of Victorian sources (by country or type of label, if available)

Graphic presentation showing the geographic distribution of threats

Comparison of the number and response of countries

Tools used:

Python (Panda, Matplotlib, Seaborn)

Excel for data cleaning and processing

Tableau/Power BI for building an interactive dashboard

Jupyter Notebook for presenting the analysis and steps

Project outcomes:
Unveiling the new Cyber New York chief, identifying the most vulnerable countries, and helping build a clear understanding of the importance of strengthening digital defense and forensic threat awareness.