Privacy Preservation in Data Centric Environment using K-Anonymity
Shrinkhala Shinghai · International Journal for Research in Applied Science and Engineering Technology · 2019
Due to the expansion in healthcare information systems, the availability of therapeutic reports has benefitted human administration organizations to inquire about work. In numerous cases, these are creating concerns while sharing helpful records. Protection methods for an unstructured helpful substance highlight on acknowledgment and ejection of individual identifiers from the substance, which may be missing for shielding security and data utility. Considering sensitive social protections information, protection security could be a noteworthy concern, when patients' restorative administration's data is utilized for investigation purposes. In this article, we have compared two methods K-anonymity and the inbuilt simulator ARX tool to ensure who can provide higher privacy on medical databases in data-intensive environments. The outcomes declare that the proposed approach has superior execution than those of the related works concerning variables such as information protection with k-anonymity.