Secure Data Provenance and Inference Control with Semantic Web

Thuraisingham, Bhavani; Cadenhead, Tyrone; Kantarcioglu, Murat; Khadilkar, Vaibhav

This book supplies step-by-step instructions on how to secure the provenance of data to make sure it is safe from inference attacks. It details the design and implementation of a policy engine for provenance of data and presents case studies that illustrate solutions in a typical distributed health care system for hospitals. Although the case studies describe solutions in the health care domain, the methods presented in the book are applicable to a range of other domains. The book also illustrates the use of Semantic Web technologies and cloud computing technologies for enhancing the scalability of solutions.

Introduction. Supporting Technologies. Security and Provenance. Access Control and Semantic Web. The Inference Problem. Inference Engines. Inferencing Examples. Cloud Computing Tools and Frameworks. Section II Secure Data Provenance. Scalable and Efficient RBAC for Provenance. A Language for Provenance Access Control. Transforming Provenance Using Redaction. Section III Inference Control. Architecture for an Inference Controller. Inference Controller Design. Provenance Data Representation for Inference Control. Queries with Regular Path Expressions. Inference Control through Query Modification. Inference and Provenance. Implementing the Inference Controller. Section IV Unifying Framework. Risk and Inference Control. Novel Approaches to Handle the Inference Problem. A Cloud-Based Policy Manager for Assured Information Sharing. Security and Privacy with Respect to Inference. Big Data Analytics and Inference Control. Unifying Framework. Summary and Directions. Appendices: Data Management Systems, Developments, and Trends. Database Management and Security.