1st Edition

Secure Data Provenance and Inference Control with Semantic Web

478 Pages

by Auerbach Publications

478 Pages

by Auerbach Publications

478 Pages

by Auerbach Publications

Also available as eBook on:

Taylor & Francis eBooks
(Institutional Purchase)Opens in new tab or window

Description

With an ever-increasing amount of information on the web, it is critical to understand the pedigree, quality, and accuracy of your data. Using provenance, you can ascertain the quality of data based on its ancestral data and derivations, track back to sources of errors, allow automatic re-enactment of derivations to update data, and provide attribution of the data source. Secure Data... Read more

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.