NOVEL RAENOPTI APPROACH FOR SECURE AND PRIVACY PRESERVING CLASSIFICATION OF HORIZONTALLY PARTITIONED MENTAL HEALTH DATA IN DISTRIBUTED ENVIRONMENT
To carry out any research the first step is data gathering, as accuracy and prediction is depending on data. In the digital era, data generated at different sectors like banking, education, healthcare center or hospitals etc. is numerous which is helpful for researcher to carry out research. However, sharing data in plain text format, may compromise privacy of data. So, to maintain the privacy and secrecy of data this paper proposes RaEnOpti Approach, where optimized and secured data will be shared with researcher. This approach uses privacy preserving data mining, Encryption techniques and Genetic Algorithm for optimization work. This paper is discussing about the work in distributed network, as the data is collected from different healthcare centers.
Privacy, Secrecy, Genetic Algorithm, Distributed Network.