Data Analytics and Decision Support for Cybersecurity, 1st ed. 2017 Trends, Methodologies and Applications Data Analytics Series

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.

Brings together and disseminates important lessons learned within a young, but surprisingly rapid field

Emphasizes the significant role of Data Science and Artificial Intelligence in overcoming crucial limitations and challenges in the IT security landscape

Bridges ideas and discussions from leading experts in academia and industry to align key directions of work that will further consolidate these fields