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Secure Data Provenance and Inference Control with Semantic Web
book

Secure Data Provenance and Inference Control with Semantic Web

by Bhavani Thuraisingham, Tyrone Cadenhead, Murat Kantarcioglu, Vaibhav Khadilkar
August 2014
Intermediate to advanced content levelIntermediate to advanced
478 pages
13h 49m
English
Auerbach Publications
Content preview from Secure Data Provenance and Inference Control with Semantic Web
Novel Approaches to Handle the Inference Problem283
constraint that classifies names and salaries at the secret level, once the names are
released to an unclassified user, the salaries cannot be released. In other words, the
salary values are regarded as secret once the names are released to an unclassified
user. erefore, the previous fact “salary is unclassified” has to be retracted once the
names are released. When reasoning with classical logics, facts cannot be retracted.
erefore, in this case a form of nonmonotonic reasoning is required. Based on the
results obtained by Yager on MP applications, it appears that such reasoning could
show promise for inference detections.
In the next section we give the background information on reasoni ...
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Publisher Resources

ISBN: 9781466569430