Differentially private model release for healthcare applications

Abstract

The evolution of technology allowed the collection of a large amount of user data, known as big data. Among all the datasets healthcare data is more sensitive. It is extremely important to protect the individual users in such datasets. Even anonymized data release is vulnerable. Hence, in this paper, we suggest a differential privacy-based model release instead of the data release. A private model release based on six machine learning classifiers namely Support Vector Machine (SVM), Random Forest algorithm, Logistic Regression, K-Nearest Neighbor, Decision Tree, and Naive Bayes are proposed. Experimental evaluation is performed using the benchmark heart disease dataset and the accuracy of the model is analyzed. The published private model can be used for the prediction of possible heart disease in patients.

Keywords:

• Differential privacy
• health care
• model release
• private model
• machine learning
• privacy preserved learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

S. Sangeetha

Ms. S. Sangeetha completed her B.E and M.E degree from Anna University, PSG College of Technology in 2007 and 2012, respectively. She is currently pursuing her PhD in Anna university. She is interested in Data mining, Big data Analytics, Machine Learning and Deep Learning. She is involved in the research field of Privacy Preservation in Data mining. She is currently working as Assistant Professor in Department of Information Technology at PSG College of Technology. She published numerous papers in international journals, book chapters and conferences.

G. Sudha Sadasivam

Dr. G. Sudha Sadasivam completed her B.E and M.E degree from PSG College of Technology under Bharathiar University in 1989 and 1991, respectively. She completed her PhD from PSG College of Technology under Bharathiar University in 2006. Her areas of interest include Compiler Design, Distributed Systems, Software Engineering, Theory of Computation and Data Analytics. She has published 5 books in compiler design, object oriented technologies and middleware technologies. She is involved in the research field of Security in computing, Data mining, Cloud computing and Distributed Systems. She is currently working as Professor and Head of Computer Science and Engineering Department at PSG College of Technology.

Ayush Srikanth

Ayush Srikanth is pursuing his B. Tech in Information Technology and is currently a third-year student of PSG College of Technology Coimbatore. In addition to his academic pursuits his research interests include Machine Learning, Data Mining, Clustering and Classification and Data Analytics.