Privacy Measure for Publishing the Data- A Case Study
Chinta Someswara Rao1, Bhadri Raju MSVS2

1China Someswara Rao, Department of CSE, SRKR Engineering College, Bhimavaram, West Godavari (A.P), India.
2Dr. Bhadri Raju MSVS, Department of CSE, SRKR Engineering College, Bhimavaram, West Godavari (A.P), India.
Manuscript received on 11 March 2014 | Revised Manuscript received on 20 March 2014 | Manuscript Published on 30 March 2014 | PP: 65-67 | Volume-3 Issue-10, March 2014 | Retrieval Number: J15420331014/14©BEIESP
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Abstract: Privacy-maintaining data release is one of the most important challenges in an information system because of the wide collection of sensitive information on the World Wide Web (WWW). Many solutions have been proposed by several researchers for privacy-maintaining data release. This paper provides an inspection of the state-of-the-art methods for privacy protection. The paper discusses novel and powerful privacy definitions which can be categorized into micro data anonymity methods and differential privacy methods for privacy maintaining data release. The methods include K-anonymity, L-diversity, T-closeness and JS-reduce defense. This paper proposes a study which will provide sequential background knowledge and provides some anonymization.
Keywords: WWW, Privacy Preserving, K-Anonymity; L-Diversity; T-Closeness; JS-Reduce.

Scope of the Article: Data Mining and Warehousing