Information anonymization is one key part of Micro information revelations as they empower approach producers to investigate the choice results of issues affecting the business there by impacting the future course of activities. Security is a key issue here in light of the fact that improper revelation of certain information stakes will hurt the prospects. Earlier methodologies of information anonymization, for example, generalization and bucketization (determined by k-obscurity, l-differing qualities) have been intended for security protecting micro information distributed which have a few confinements like Generalization's powerlessness to handle high dimensional information and Bucketization disappointment to keep up clear detachment between semi distinguishing characteristics and touchy properties incited the advancement of a novel strategy called Slicing, which segments the information both evenly and vertically. Albeit Slicing accomplishes better information utility and secrecy contrasted with earlier strategies, its delicate characteristic exposures are focused around irregular gathering, which is not extremely powerful as haphazardly creating the relationship between section estimations of a pail fundamentally brings down information utility. Consequently, we propose to supplant arbitrary gathering with more powerful tuple gathering calculations, for example, Tuple Space Search calculation focused around hashing methods. The figured and got cut information from high dimensional touchy characteristics focused around the proposed procedure offers noteworthy execution climb. An attainable down to earth usage on dynamic information approves our case.