An Enhanced Method for Privacy Preservation in Data Publishing

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 internet. A number of solutions have been designed 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 microdata 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 an enhanced method which will prevents sequential background knowledge attack and provides some anonymization also.