Data Analytics for Cybersecurity

Vandana Janeja is Professor and Chair of the Information Systems department at the University of Maryland, Baltimore County. Most recently, she also served as an expert at the National Science Foundation supporting data science activities in the Directorate for Computer and Information Science and Engineering (CISE) (2018-2021). Her research interests include discovering knowledge in presence of data heterogeneity. Her research projects include anomaly detection in network communication data, human behavior analytics in heterogeneous device environments, geo spatial context for IP reputation scoring, spatio-temporal analysis across heterogeneous data, ethical thinking in data science. She has been funded through state, federal and private organizations.

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;