Secure data provenance and inference control with semantic web / Bhavani Thuraisingham, Tyrone Cadenhead, Murat Kantarcioglu, Vaibhav Khadilkar.

Format:

Book

Author/Creator:

Thuraisingham, Bhavani M., author.

Cadenhead, Tyrone, author.

Kantarcioglu, Murat, author.

Khadilkar, Vaibhav, author.

Language:

English

Subjects (All):

Semantic Web.

Database security.

Inference.

Authentication.

Physical Description:

1 online resource (462 p.)

Edition:

1st ed.

Place of Publication:

Boca Raton : CRC Press, [2015]

Language Note:

English

Summary:

With the explosion of information on the web, it is critical to understand the provenance of the data, which includes its pedigree, quality, and accuracy. At the same time, the provenance data must be secured. This book describes a detailed step-by-step approach to securing provenance data and ensuring that the data cannot be subject to inference attacks. It presents solutions with case studies in the healthcare domain, describes the design and implementation of a policy engine for provenance, and demonstrates the use of semantic web technologies as well as cloud computing technologies for enhancing the scalability of solutions-- Provided by publisher.

Contents:

Front Cover; Contents; Preface; Acknowledgments; Authors; Permissions; Chapter 1: Introduction; Chapter 2: Security and Provenance; Chapter 3: Access Control and Semantic Web; Chapter 4: The Inference Problem; Chapter 5: Inference Engines; Chapter 6: Inferencing Examples; Chapter 7: Cloud Computing Tools and Frameworks; Chapter 8: Scalable and Efficient RBAC for Provenance; Chapter 9: A Language for Provenance Access Control; Chapter 10: Transforming Provenance Using Redaction; Chapter 11: Architecture for an Inference Controller; Chapter 12: Inference Controller Design

Chapter 13: Provenance Data Representation for Inference ControlChapter 14: Queries with Regular Path Expressions; Chapter 15: Inference Control through Query Modification; Chapter 16: Inference and Provenance; Chapter 17: Implementing the Inference Controller; Chapter 18: Risk and Inference Control; Chapter 19: Novel Approaches to Handle the Inference Problem; Chapter 20: A Cloud-Based Policy Manager for Assured Information Sharing; Chapter 21: Security and Privacy with Respect to Inference; Chapter 22: Big Data Analytics and Inference Control; Chapter 23: Unifying Framework

Chapter 24: Summary and DirectionsAppendix A: Data Management Systems, Developments, and Trends; Appendix B: Database Management and Security; Appendix C: A Perspective of the Inference Problem; Appendix D: Design and Implementation of a Database Inference Controller; Back Cover

Notes:

Description based upon print version of record.

Includes bibliographical references at the end of each chapters.

Description based on print version record.

ISBN:

1-04-005742-X

0-367-37844-2

0-429-10195-3

1-4665-6943-3

9780429101953

OCLC:

889309886