Certain investigations on privacy preserving data mining using perturbation for pharmaceutical drugs

Abstract

Human society faces different challenges in form of novel diseases in day to day life. Every year various diseases are being identified from human body. In the procurement of those diseases, different pharmaceutical products are launched by the medical society. Also, consecutive treatments are recommended by the medical practitioners. Each of the drugs and treatment has different curing rate. The medical organizations maintain huge data set with respect to the patients and the corresponding treatments provided. Such huge database is being utilized by various organizations to generate intelligence on the nature of the treatments offered and helps to perform market analysis. The medical data set contains variety of information, which includes medical, personal and purchase data. Such data consist of sensitive information which associates with the private information of employees of medical organization and the customers. The organizations hold the responsibility in maintaining sensitive items and information of customers. newlineThe data maintained by the organizations has been shared among different parties towards intelligence generation and to support decision making. By using the data set, the medical practitioner can identify the effective treatment which is more successful against a disease. According to this, the identity and personal information of the customer and patient has to be hidden in the view of third party. Similarly, when the data set is shared with the third party organization, the identity of the user must be hidden to support intelligence generation. Using the data set, the organization or pharmaceutical industry can be able to identify the fast moving drugs. However, the identity and personal information of the users must be hidden from the third party and not to be exposed to the external world. newline