This data-oriented approach to studying cyber threats shows in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity.
Inhaltsverzeichnis
Preface; 1. Introduction; 2. Understanding sources of cybersecurity data; 3. Introduction to data mining: clustering, classification and association rule mining; 4. Big data analytics and its need for cybersecurity: advanced DM and complex data types from cybersecurity perspective; 5. Types of Cyber Attacks; 6. Anomaly Detection for cyber security; 7. Anomaly Detection; 8. Cybersecurity through Time Series and Spatial data; 9. Cybersecurity through Network and Graph Data; 10. Human Centered Data Analytics for Cyber security; 11. Future directions in Data Analytics for Cybersecurity; References; Index;