Secure Data Provenance and Inference Control with Semantic Web
Published on 1. August 2014
478 pages
978-1-4665-6944-7 (ISBN)
Description
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.
More details
Language
English
Place of publication
Philadelphia, PA
United States
Publishing group
Taylor & Francis Inc
Target group
Professional and scholarly
File size
6,83 MB
ISBN-13
978-1-4665-6944-7 (9781466569447)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Bhavani Thuraisingham | Tyrone Cadenhead | Murat Kantarcioglu
Secure Data Provenance and Inference Control with Semantic Web
Book
09/2019
1st Edition
CRC Press
€73.03
Shipment within 15-20 days
Bhavani Thuraisingham | Tyrone Cadenhead | Murat Kantarcioglu
Secure Data Provenance and Inference Control with Semantic Web
Book
08/2014
1st Edition
Auerbach
€165.50
Shipment within 15-20 days
Persons
Thuraisingham, Bhavani; Cadenhead, Tyrone; Kantarcioglu, Murat; Khadilkar, Vaibhav
Content
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.
