Design And Implementation Of Medical Information Hidden System

Nowadays, micro-data are increasingly asked to make their raw data electronically available for research purpose or business purpose. However, such disclosures raise serious privacy and secret concerns as the data may contain much personal and organizational information. Usually, these data will be anonymized before being published to protect the privacy and secret.This paper aims at designing and implementing a medical information anonymous system. This system uses k-anonymous technology to anonymize micro-data, and uses three different searching algorithms to find Quasi-Identifier (QI). Many tests are done to compare the performance of these algorithms. The testing result can be used to give a reference when choosing searching algorithm.This article researches and studies the existing information anonymizing methods. After comparing the executing and anonymous performance of different methods, the Samarati's method in K-Anonymity model is chosen as the anonymize method in medical information hidden system. At the same time, by analysing the specific business requirements of data anonymous in medical industries and the use-case model, the business process and functional and non-functional requirements of the system are well studied. The module division of Medical Information Hidden System is done based on the requirements analysis, and the system is also designed and modelled. The core problem of the whole information hidden system, Quasi-Identifier searching, is also modelled. This article proposes three possible searching methods to solve this core problem and find a better information hidden solution. After implementing all the functional modules, many testing technologies are used to verify the stability and robustness of the whole system. In this process, tests are done focused on the information hidden module and QI searching module with a lot of testing data. By analysing and comparing the testing results, finally, a better approach is found to have better information hidden performance than others. By applying this method, the information need to be anonymized can be found faster and more accurate, and better anonymized information will be created.