PRIVACY PREVENTION OF TEXTUAL AND NUMERIC SENSITIVE INFORMATION BY K-ANONYMITY AND PERTURBATION TECHNIQUE

Abstract

With the increase of digital data on servers different approach of data mining is done. This lead to important issue of proving privacy to the unfair information against any person, place, community etc. So Privacy preserving mining come in existence. This paper provide privacy for sensitive rule that discriminate data on the basis of frequency. So finding of those rules and suppression is done. Perturbation technique is use for the hiding sensitive rules. Experiment is done on real adult dataset for different ratio. Results shows that proposed work is better in maintaining the Perturbation Percentage, Individual Privacy at last suppress rules while other rules are remain unaffected.