The Definitive Security Data Science and Machine Learning Guide
📜 Abstract
This is the Definitive Security Data Science and Machine Learning Guide. It includes books, tutorials, presentations, blog posts, and research papers about solving security problems using data science.
✨ Summary
The document is a curated resource guide rather than a conventional research paper. It organizes research papers, books, tutorials, presentations, datasets, blogs, and open-source projects concerning the application of data science and machine learning to cybersecurity, including intrusion detection, malware analysis, data collection, vulnerability analysis, privacy, cybercrime, and deep learning.
Evidence of influence indicates that the guide was used as an educational and research-discovery resource. It was listed as suggested course material for the University of Texas at Dallas course “Advanced Topics in Internet Measurement and Network Security” in both 2017 and 2018 syllabi. (dox.utdallas.edu) It was also included in the Papers We Love collection of research-paper resources and referenced by independent cybersecurity and machine-learning blogs as a compilation of relevant papers, books, datasets, and presentations. (gitextract.com) The available evidence supports its role as a curated bibliography and teaching aid; it does not indicate that the guide itself introduced a new research method or technical result.