hija/MalwareDataScience
Malware Data Science Reading Diary / Notes
This project helps security analysts and researchers understand and apply data science techniques to malware analysis. It provides summaries and code examples that illustrate how to analyze malware using static, dynamic, and machine learning methods. You'll gain practical insights into identifying attack campaigns, evaluating detection systems, and building neural network detectors.
130 stars. No commits in the last 6 months.
Use this if you are a cybersecurity professional or data scientist looking to deepen your understanding of malware analysis and build effective detection systems using data science.
Not ideal if you're looking for a production-ready malware analysis tool or a comprehensive data science textbook.
Stars
130
Forks
35
Language
Jupyter Notebook
License
MIT
Category
Last pushed
May 05, 2019
Commits (30d)
0
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