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:
ORGANIZATIONS
collect and analyze consumer data to improve their services. Access Control
Mechanisms (ACM) are used to ensure that only authorized information is
available to users. However, sensitive information can still be misused by
authorized users to compromise the privacy of consumers. 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. Existing
workload aware anonymization techniques minimize the imprecision aggregate for
all queries and the imprecision added to each permission/query in the
anonymized micro data is not known. Making the privacy requirement more
stringent (e.g., increasing the value of k or l) results in additional
imprecision for queries.
DISADVANTAGES OF
EXISTING SYSTEM:
v There
is no Privacy for users Data.
v
The sensitive information, even after
the removal of identifying attributes, is still susceptible to linking attacks
by the authorized users.
PROPOSED SYSTEM:
The
heuristics proposed in this paper for accuracy-constrained privacy-preserving
access control are also relevant in the context of workload-aware
anonymization. The anonymization for continuous data publishing has been studied
in literature. In this paper the focus is on a static relational table that is
anonymized only once. To exemplify our approach, role-based access control is
assumed. However, the concept of accuracy constraints for permissions can be
applied to any privacy-preserving security policy, e.g., discretionary access
control.
ADVANTAGES OF PROPOSED
SYSTEM:
v
Accuracy-constrained privacy-preserving
access.
v
It maintains data’s in a secure manner.
SYSTEM CONFIGURATION:-
HARDWARE REQUIREMENTS:-
Processor - Pentium –IV
Speed - 1.1 Ghz
RAM - 512 MB(min)
Hard Disk - 40
GB
Key Board - Standard
Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - LCD/LED
SOFTWARE
REQUIREMENTS:
Operating
system : Windows XP.
Coding
Language : JAVA
Data
Base : MySQL
Tool : Netbeans
REFERENCE:
Zahid
Pervaiz, Walid G. Aref, Senior Member, IEEE, Arif Ghafoor, Fellow, IEEE, and
Nagabhushana Prabhu, “Accuracy-Constrained
Privacy-Preserving Access Control Mechanism for Relational Data” IEEE
TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 26, NO. 4, APRIL 2014 795
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