Data anonymization through generalization using map reduce on cloud

Now a day´s cloud computing provides lot of computation power and storage capacity to the users can be share their private data. To providing the security to the users sensitive data is challenging and difficult one in a cloud environment. K-anonymity approach as far as used for providing privacy to users sensitive data, but cloud can be greatly increases in a big data manner. In the existing, top-town specialization approach to make the privacy of users sensitive data. When the scalability of users data increase means top-town specialization technique is difficult to preserve the sensitive data and provide security to users data. Here we propose the specialization approach through generalization to preserve the sensitive data and provide the security against scalability in an efficient way with the help of map-reduce. Our approach is founding better solution than existing approach in a scalable and efficient way to provide security to users data.