Indian Journal of Science and Technology
DOI: 10.17485/ijst/2017/v10i10/109294
Year: 2017, Volume: 10, Issue: 10, Pages: 1-5
Original Article
Shivaprakash Ranga* , Balakrishnan and Nageswara Guptha
Department of ISE, Sri Venkateshwara College of Engineering, Vidyanagara Cross, Bangalore International Airport Road, Bettahalasur Post Yelahanaka, Bengaluru – 562157, India; [email protected], Bala.k.btech[email protected], [email protected]
*Author for correspondence
Shivaprakash Ranga
Department of ISE, Sri Venkateshwara College of Engineering, Vidyanagara Cross, Bangalore International Airport Road, Bettahalasur Post Yelahanaka, Bengaluru – 562157, India; [email protected]
Objectives: To propose an approach thereby only data owner can view the records by fetching from cloud using decryption and the anonymized records can be made available for the researchers to understand the patterns for a particular disease. Methods: Proposed work is implemented by using Hadoop Map-Reduce Framework. To offer personal privacy, it uses two attributes: Sensitive Disclosure Flag (SDF) and Sensitive Weight (SW) which is marked on the basis of personal privacy. Findings: Only data owner can view the records by fetching from cloud using decryption, the anonymized records are made available for the researchers to understand the patterns for a particular disease. Our proposed method is the enhancement of previous anonymity techniques, initially each patient IDs in the medical record table is changed using encryption method and then the records are generalized to make anonymity and at the end, original and anonymized data records are stored in cloud which eliminates the big data storage problem at local system.
Keywords: BigData, Map-Reduce, Personal Anonymization
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