Secure Data Provenance and Inference Control with Semantic Web

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A01=Bhavani Thuraisingham
A01=Murat Kantarcioglu
A01=Tyrone Cadenhead
A01=Vaibhav Khadilkar
access
Access Control Models
Access Control Policy
Age Group_Uncategorized
Age Group_Uncategorized
Author_Bhavani Thuraisingham
Author_Murat Kantarcioglu
Author_Tyrone Cadenhead
Author_Vaibhav Khadilkar
automatic-update
Category1=Non-Fiction
Category=UR
cloud data privacy
cloud provenance management framework
controller
COP=United Kingdom
data lineage
Delivery_Delivery within 10-20 working days
engine
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
graph
Graph Pattern
Graph Rewriting
healthcare informatics
Inference Control
Inference Controller
Inference Engine
Inference Problem
Inference Strategies
information security
Language_English
OPM
PA=Available
policies
Price_€100 and above
problem
Provenance Data
Provenance Graph
Provenance Information
PS=Active
queries
Query Modification
RDF Data
RDF Query
RDF Query Language
RDF Triple
regular
role-based access control
Secure Data Provenance
semantic reasoning
Semantic Web
Semantic Web Technologies
Sensitive Information
softlaunch
sparql
SPARQL Queries
SWRL Rule
technologies
Triple Pattern

Product details

  • ISBN 9781466569430
  • Weight: 804g
  • Dimensions: 156 x 234mm
  • Publication Date: 01 Aug 2014
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
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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 Provenance and Inference Control with Semantic Web supplies step-by-step instructions on how to secure the provenance of your 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, you can easily apply the methods presented in the book to a range of other domains.

The book describes the design and implementation of a policy engine for provenance and demonstrates the use of Semantic Web technologies and cloud computing technologies to enhance the scalability of solutions. It covers Semantic Web technologies for the representation and reasoning of the provenance of the data and provides a unifying framework for securing provenance that can help to address the various criteria of your information systems.

Illustrating key concepts and practical techniques, the book considers cloud computing technologies that can enhance the scalability of solutions. After reading this book you will be better prepared to keep up with the on-going development of the prototypes, products, tools, and standards for secure data management, secure Semantic Web, secure web services, and secure cloud computing.

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

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