Data perturbation using fuzzy logic to preserve privacy

The latest advances in the field of information technology have increased enormous growth in the data collection in recent days. Individual´s data are shared for business or legal reasons, which contain confidential information. Sharing data is a mutual benefit for business growth. The need to preserve privacy has become a challenging problem in privacy preserving data mining. In this paper we deal with a data analysis system having sensitive information. The data having confidential attributes are perturbed or distorted using fuzzy logic. Fuzzy logic is used to protect individual´s data to hide details before publishing it. The paper focuses on the idea of distorting original dataset using sbased fuzzy membership function to produce distorted dataset. Initially data is owned by an authorized user performs distortion .The Authorized user having original dataset distorts using fuzzy membership function and publish the distorted data to the Analyst. The Analysts performs data mining techniques on the distorted dataset. Accuracy of Classifiers generated on distorted data is relative to the original, thus privacy is achieved. Comparisons of various classifiers are generated on the original and distorted datasets.