A Privacy Preserving Clustering On Alphanumeric Data
Patel Kevin, Patel Hiteshree, Patel Krishna C., Patel Krishna J., Mr.Kaushal Patel, Sheshang Degadwala · International Journal of Scientific Research in Science Engineering and Technology · 2018
Huge volume of detailed data is collected and analyzed by applications using data mining, sharing of these data is beneficial to the unauthorized persons. On the other hand, it is an important asset to business organization and government for decision making process. At the same time analyzing such data open threats to privacy if privacy is not preserved properly. Our project aims to reveal the information by protecting sensitive data. We are using three perturbation techniques to preserve the privacy of data. Perturbed dataset does not reveal the original data and also does not change the analysis results. Hence, privacy is preserved.