F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes

With the advent of smart health, cities, and grids, amount data has grown swiftly. When collected is published for valuable information mining, privacy turns out to be a key matter due presence sensitive information. Such comprises either single attribute (an individual only one attribute) or multiple attributes can have attributes). Anonymization sets with presents some unique problems correlation among these attributes. Artificial intelligence techniques help publishers in anonymizing such data. To best our knowledge, no fuzzy logic-based model been proposed until now preservation In this paper, we propose novel preserving F-Classify that uses logic classification quasi-identifier Classes are defined based on rules, every tuple assigned its class according value. The working Algorithm also verified using HLPN. A wide range experiments healthcare acknowledged surpasses counterparts terms utility. Being artificial intelligence, it lower execution time than other approaches.