Book contents
- Data Analytics for Cybersecurity
- Data Analytics for Cybersecurity
- Copyright page
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Understanding Sources of Cybersecurity Data
- 3 Introduction to Data Mining
- 4 Big Data Analytics and Its Need for Cybersecurity
- 5 Types of Cyberattacks
- 6 Anomaly Detection for Cybersecurity
- 7 Anomaly Detection Methods
- 8 Cybersecurity through Time Series and Spatial Data
- 9 Cybersecurity through Network and Graph Data
- 10 Human-Centered Data Analytics for Cybersecurity
- 11 Future Directions in Data Analytics for Cybersecurity
- References
- Index
4 - Big Data Analytics and Its Need for Cybersecurity
Advanced DM and Complex Data Types from Cybersecurity Perspective
Published online by Cambridge University Press: 10 August 2022
- Data Analytics for Cybersecurity
- Data Analytics for Cybersecurity
- Copyright page
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Understanding Sources of Cybersecurity Data
- 3 Introduction to Data Mining
- 4 Big Data Analytics and Its Need for Cybersecurity
- 5 Types of Cyberattacks
- 6 Anomaly Detection for Cybersecurity
- 7 Anomaly Detection Methods
- 8 Cybersecurity through Time Series and Spatial Data
- 9 Cybersecurity through Network and Graph Data
- 10 Human-Centered Data Analytics for Cybersecurity
- 11 Future Directions in Data Analytics for Cybersecurity
- References
- Index
Summary
Focusing on the big data elements of cybersecurity, this chapter looks at the landscape of the big data technologies and the complexities of the different types of data, including spatial and graph data. It outlines examples in these complex data types and how they can be evaluated using data analytics.
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- Information
- Data Analytics for Cybersecurity , pp. 60 - 77Publisher: Cambridge University PressPrint publication year: 2022