Secure Data Provenance and Inference Control with Semantic Web

Couverture
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 attribu
 

Table des matières

Introduction
1
Security and Provenance
19
Access Control and Semantic Web
29
The Inference Problem
43
Inference Engines
53
Inferencing Examples
63
Cloud Computing Tools and Frameworks
81
Scalable and Efficient RBAC for Provenance
99
Inference and Provenance
219
Implementing the Inference Controller
231
Risk and Inference Control
261
Novel Approaches to Handle the Inference Problem
273
A CloudBased Policy Manager for Assured Information Sharing
291
Security and Privacy with Respect to Inference
309
Big Data Analytics and Inference Control
325
Unifying Framework
333

A Language for Provenance Access Control
119
Transforming Provenance Using Redaction
143
Architecture for an Inference Controller
169
Inference Controller Design
183
Provenance Data Representation for Inference Control
195
Queries with Regular Path Expressions
201
Inference Control through Query Modification
209
Summary and Directions
345
Data Management Systems Developments and Trends
353
Database Management and Security
371
A Perspective of the Inference Problem
397
Design and Implementation of a Database Inference Controller
407
Back Cover
429
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À propos de l'auteur (2014)

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

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