Data analytics and decision support for cybersecurity: trends, methodologies and applications

摘要

Data analytics and decision support have recently influenced many fields; cybersecurity is one of them. This book, published in Springer's "Data Analytics" series, is on data analytics and decision support applications for cybersecurity. The book has two parts. The first part comprises seven regular chapters, whereas the second part includes two invited chapters. The first part begins with chapter 1, which "focuses on anomaly-based network intrusion detection." The authors use data mining techniques to overcome the difficulties in utilizing anomaly-based network intrusion detection. Chapter 2 studies "the problem of detecting insider threats in organizations." It looks at some of the key challenges confronted by insider threat detection systems, for example, the hardships faced in cutting down on false alarms. The chapter demonstrates the benefits of pairing visual analytics with machine learning to arrive at well-informed decisions.