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Full Description
As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing 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.
Contents
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;