ABSTRACT
This conclusion presents some closing thoughts on the concepts covered in part 2 of this book. The part describes data science technologies for cyber security applications. It discusses data mining for malware detection and data mining tools for malware detection. In particular, feature extraction using n-gram analysis and the hybrid feature retrieval model is discussed. The part also discusses the experiments and datasets and what stream analytics is about and also discusses an approach for detecting malware detection. It describes algorithms for detecting novel classes (of malware) and an architecture of the system. The part provides a survey of insider threat and stream mining and discusses scalability issues with big data/data science techniques.
