ABSTRACT
Part I, consisting of four chapters described supporting technologies for secure data science. In Chapter 2, we provided an overview of discretionary security policies in database systems. We started with a discussion of access control policies, including authorization policies and role-based access control policies. Then we discussed administration policies. We briefly discussed identification and authentication. We also discussed auditing issues as well as views for security. Next, we discussed policy enforcement as well as SQL extensions for specifying policies as well as provided an overview of query modification. Finally, we provided a brief overview of data privacy aspects. In Chapter 3, we provided an overview of data mining for cyber security applications. In particular, we discussed various data mining techniques and described their applications to detect intrusion detection and insider threat detection. Chapter 4 introduced the notions of the cloud, semantic web, and social network technologies. This is because some of the experimental systems discussed in Part IV utilize these technologies. We first discussed concepts in cloud computing, including aspects of virtualization, deployment models, and cloud functions. We also discussed technologies for the semantic web, including XML, RDF, Ontologies, and OWL. Finally, we discuss social network analytics and security. In Chapter 5, we discussed big data security and privacy. First, we discussed security and privacy issues and then discussed some of the research challenges.
