Accuracy-Constrained Privacy-Preserving Access Control
Mechanism for Relational Data
ABSTRACT:
Access control
mechanisms protect sensitive information from unauthorized users. However, when
sensitive information is shared and a Privacy Protection Mechanism (PPM) is not
in place, an authorized user can still compromise the privacy of a person
leading to identity disclosure. A PPM can use suppression and generalization of
relational data to anonymize and satisfy privacy requirements, e.g.,
k-anonymity and l-diversity, against identity and attribute disclosure.
However, privacy is achieved at the cost of precision of authorized
information. In this paper, we propose an accuracy-constrained privacy-preserving
access control framework. The access control policies define selection
predicates available to roles while the privacy requirement is to satisfy the
k-anonymity or l-diversity. An additional constraint that needs to be satisfied
by the PPM is the imprecision bound for each selection predicate. The
techniques for workload-aware anonymization for selection predicates have been
discussed in the literature. However, to the best of our knowledge, the problem
of satisfying the accuracy constraints for multiple roles has not been studied
before. In our formulation of the aforementioned problem, we propose heuristics
for anonymization algorithms and show empirically that the proposed approach
satisfies imprecision bounds for more permissions and has lower total
imprecision than the current state of the art.
EXISTING SYSTEM:
The concept of
privacy-preservation for sensitive data can require the enforcement of privacy
policies or the protection against identity disclosure by satisfying some
privacy requirements. Investigate privacy-preservation from the
anonymityaspect. The sensitive information, even after the removal of
identifying attributes, is still susceptible to linking attacks by the
authorized users.
DISADVANTAGES
OF EXISTING SYSTEM:
Ø Minimize the imprecision aggregate for all queries .
Ø The imprecision added to each permission/query in the
anonymized micro data is not known.
Ø Not satisfying accuracy constraints for individual
permissions in a policy/workload.
PROPOSED SYSTEM:
Ø The heuristics proposed in this paper for accuracy
constrained privacy-preserving access control are also relevant in the context
of workload-aware anonymization.
Ø The framework is a combination of access control and
privacy protection mechanisms.
Ø The access control mechanism allows only authorized
query predicates on sensitive data.
Ø The privacy preserving module anonymizes the data to
meet privacy requirements and imprecision constraints on predicates set by the
access control mechanism.
ADVANTAGES
OF PROPOSED SYSTEM:
·
Formulate
the accuracy and privacy constraints.
·
Concept
of accuracy-constrained privacy-preserving access control for relational data.
·
Approximate
the solution of the k-PIB problem and conduct empirical evaluation.
SYSTEM
REQUIREMENTS:
HARDWARE REQUIREMENTS:
Ø
System : Pentium IV 2.4 GHz.
Ø
Hard Disk :
40 GB.
Ø
Floppy Drive : 1.44
Mb.
Ø
Monitor : 15
VGA Colour.
Ø
Mouse :
Logitech.
Ø Ram : 512 Mb.
SOFTWARE
REQUIREMENTS:
Ø Operating system : Windows
XP/7.
Ø Coding Language : JAVA/J2EE
Ø IDE : Netbeans 7.4
Ø Database : MYSQL
REFERENCE:
Zahid Pervaiz,
Walid G. Aref, Senior Member, Arif Ghafoor, Fellow, and Nagabhushana Prabhu,“Accuracy-Constrained
Privacy-Preserving Access Control Mechanism for Relational Data”, IEEE
TRANSACTIONS, VOL. 26, NO. 4, APRIL 2014.
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