The book illustrates the inter-relationship between several data
management, analytics and decision support techniques and methods
commonly adopted in Cybersecurity-oriented frameworks. The recent advent
of Big Data paradigms and the use of data science methods, has resulted
in a higher demand for effective data-driven models that support
decision-making at a strategic level. This motivates the need for
defining novel data analytics and decision support approaches in a
myriad of real-life scenarios and problems, with Cybersecurity-related
domains being no exception.
This contributed volume comprises nine chapters, written by leading
international researchers, covering a compilation of recent advances in
Cybersecurity-related applications of data analytics and decision
support approaches. In addition to theoretical studies and overviews of
existing relevant literature, this book comprises a selection of
application-oriented research contributions. The investigations
undertaken across these chapters focus on diverse and critical
Cybersecurity problems, such as Intrusion Detection, Insider Threats,
Insider Threats, Collusion Detection, Run-Time Malware Detection,
Intrusion Detection, E-Learning, Online Examinations, Cybersecurity
noisy data removal, Secure Smart Power Systems, Security Visualization
and Monitoring.
Researchers and professionals alike will find the chapters an essential
read for further research on the topic.
