System and method for database privacy protection
AssigneeTata Consultancy Services Limited
InventorsArijit Ukil, Jaydip Sen
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Abstract
The invention relates to a system and a method for privacy preservation of sensitive attributes stored in a database. The invention reduces the complexity and enhances privacy preservation of the database by determining the distribution of sensitive data based on Kurtosis measurement. The invention further determines and compares the optimal value of k-sensitive attributes in k-anonymity data sanitization model with the optimal value of l sensitive attributes in l diversity data sanitization model using adversary information gain. The invention reduces the complexity of the method for preserving privacy by applying k anonymity only, when the distribution of the sensitive data is leptokurtic and optimal value of k is greater than the optimal value of l.
Claims8
A method for reducing complexity and enhancing privacy preservation of a database with a plurality of sensitive attributes, the method comprising processor implemented steps of:
- determining a distribution pattern of the sensitive attributes by applying Kurtosis measurement of the corresponding data of the database to ascertain whether the distribution pattern of the sensitive data is leptokurtic;
- determining an adversary information gain for the k-anonymity data sanitization model and the adversary information gain for a k-anonymity l-diversity data sanitization model;
- comparing the adversary gain of the k-anonymity data sanitization model with the adversary information gain of the k-anonymity l-diversity data sanitization model till the adversary information gain of the k-anonymity data sanitization model becomes equal to the adversary information gain of the k-anonymity l-diversity data sanitization model;
- determining an optimal value of l for performing l-diversity based data sanitization on the sensitive records and computing an optimal value of k for performing k-anonymity based data sanitization on the sensitive attributes;
- and
- performing privacy preservation of the sensitive attributes by only k-anonymity data sanitization model when k is greater than l and the distribution pattern is leptokurtic such that the k-anonymity provides the same amount of privacy protection as provided by k-anonymity l-diversity data sanitization model.
A system for reducing complexity and enhancing privacy preservation of a database with a plurality of sensitive attributes, the system comprising:
- a computer readable medium for storing the corresponding data of the database storing k sensitive attributes of a k-anonymity data sanitization model and l sensitive attributes of an l-diversity data sanitization model;
- a control device configured for operating a calculating module for determining a distribution pattern of the sensitive attributes through Kurtosis measurement of the corresponding data of the database, for determining an optimal value of a k sensitive attributes in a k-anonymity data sanitization model an optimal value of l sensitive attributes in an l-diversity data sanitization model and for determining an adversary information gain of k-anonymity data sanitization model and an adversary information gain of k-anonymity l-diversity data sanitization model;
- a comparator for comparing the adversary information gain of k-anonymity data sanitization model with the adversary information gain of k-anonymity l-diversity data sanitization model and for comparing the optimal value of the l sensitive attributes in the l-diversity data sanitization model with the optimal value of the k sensitive attributes in the k-anonymity data sanitization model and storing the same in the computer readable medium;
- and
- a processor communicatively coupled with the comparator for performing privacy preservation of the sensitive attributes with leptokurtic distribution by applying the k-anonymity data sanitization model, if the optimal value of k sensitive attributes in the k-anonymity sanitization method is greater than the optimal value of l sensitive attributes in the l-diversity sanitization method;
- and
- an evaluation module for evaluating the reduction in complexity of k-anonymity data sanitization model for performing the privacy preservation of the sensitive data.
Dependencies are inferred from the claim text.