Privacy Preserving Based on PCA Transformation Using Data Perturbation Technique

Maintain confidentiality, privacy and security research in data mining (PPDM) is one of the biggest trends. Recent advances in data collection, data dissemination and related technologies have inaugurated a new era of research where existing data mining algorithms should be reconsidered from a different point of view, this of privacy preservation. We propose a simple PCA based transformation approach for various datasets to preserve privacy and maintain accuracy based on clustering. A privacy soil, the proposal to convert the data into nature, conservation saves. The accuracy of clustering before and after privacy preserving transformation was estimated. KeywordsPrivacy; PCA; K-means clustering