Module 1: Background for Big Data Security and Privacy

• Topics include: (i) Cyber Security; (ii) Secure Data Management; (iii) malware, (iv) Data Mining for Malware Detection; (v) Data Privacy, (vi) Big Data Management and Analytics, (vii) Semantic web

Module 2: Big Data Security and Privacy Concepts

• Topics include (i) Big Data Security and Privacy: Developments and Directions; (ii) Secure Data Science/AI (iii) Big Data Inference Controllers. (iv) Big Data Tools and Security

Module 3: Infrastructures for Big Data Security and Privacy - Cloud

• Topics include (i) Introduction to Secure SOA and Cloud Computing, (ii) Secure Cloud Computing for Assured Information Sharing, (iii) Access Control for the Cloud, (iv) Hadoop and MapReduce Security

Module 4: Big Data Security and Privacy Functions

• Topics include (i) Access Control Model for Big Data, (ii) Secure Big Data Query Processing with HIVE, (iii) Secure Big Data Processing with Semantic Web, (iv) Secure Big Data Storage, (v) Privacy model for Big Data, (vi) Big Data Governance, (vii) Example Secure Big Data System

Module 5: Big Data Security and Privacy Applications – Social Media

• Topics include (i) Security and Privacy for Online Social Networks, (ii) Attacks on Social Media,  (iii) Social Media Governance, (iv) Fake news detection. In addition, the representation of social media using semantic web will also be discussed  to provide context.

Module 6: Directions for Big Data Security and Privacy

• Topics include (i) Data Science for Cyber Security, (ii) Adversarial Machine Learning, (iii) Cloud computing for implementing machine learning techniques or malware detection, (iv) Data Science Applications for IoT Security, (iv) Blockchain, Data Science and Security, (v) Security and Knowledge Graphs, (vi) Quantum Information Processing for Big Data.