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.
Rezensionen / Stimmen
'The intersection of cybersecurity and big data is an operational and analytical capability still very much in its infancy. Data Analytics for Cybersecurity is perfectly positioned as a useful and necessary primer on the subject by exploring this relationship in clear, understandable language and imparts to readers not only the fundamentals of cybersecurity analytics from an academic perspective, but also, if not perhaps more importantly, how this capability relates to and can enhance cybersecurity in actual practice.' Richard Forno, University of Maryland Baltimore County 'Dr. Janeja shows us how data analytics can be used to predict, identify and intercept threats, solving difficult cybersecurity problems in the process. As a Professor and cybersecurity professional, I am thrilled for the prospect of teaching this material to my students and applying it to the industry at large. Simply put, this is the cybersecurity book I've been looking for.' Faisal Quader, Technuf LLC
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Illustrationen
Worked examples or Exercises
Maße
Höhe: 235 mm
Breite: 157 mm
Dicke: 16 mm
Gewicht
ISBN-13
978-1-108-41527-9 (9781108415279)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
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.
Autor*in
University of Maryland, Baltimore County
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;
