Secure Multi-Party linear Regression

Increasing efficiency in hospitals is of particular importance. Studies that combine data from multiple hospitals/data holders can tremendously improve the statistical outcome and aid in identifying efficiency markers. However, combining data from multiple sources for analysis poses privacy risks. A number of protocols have been proposed in the literature to address the privacy concerns; however they do not fully deliver on either privacy or complexity. In this paper, we present a privacy preserving linear regression model for the analysis of data coming from several sources. The protocol uses a semi-trusted third party and delivers on privacy and complexity.

[1]  J. Brian Gray,et al.  Introduction to Linear Regression Analysis , 2002, Technometrics.

[2]  S. Fienberg,et al.  Secure multiple linear regression based on homomorphic encryption , 2011 .

[3]  Linda Argote,et al.  Individual Experience and Experience Working Together: Predicting Learning Rates from Knowing Who Knows What and Knowing How to Work Together , 2005, Manag. Sci..

[4]  Yvo Desmedt,et al.  Threshold Cryptosystems , 1989, CRYPTO.

[5]  Yehuda Lindell,et al.  Privacy Preserving Data Mining , 2002, Journal of Cryptology.

[6]  Yunghsiang Sam Han,et al.  Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification , 2004, SDM.

[7]  Henri Cohen,et al.  A course in computational algebraic number theory , 1993, Graduate texts in mathematics.

[8]  Gary P. Pisano,et al.  Organizational Differences in Rates of Learning: Evidence from the Adoption of Minimally Invasive Cardiac Surgery , 2001, Manag. Sci..

[9]  Stratis Ioannidis,et al.  Privacy-Preserving Ridge Regression on Hundreds of Millions of Records , 2013, 2013 IEEE Symposium on Security and Privacy.

[10]  Shuguo Han,et al.  Privacy-Preserving Linear Fisher Discriminant Analysis , 2008, PAKDD.

[11]  Kouichi Sakurai,et al.  Distributed Paillier Cryptosystem without Trusted Dealer , 2010, WISA.

[12]  Murat Kantarcioglu,et al.  A secure distributed logistic regression protocol for the detection of rare adverse drug events , 2012, J. Am. Medical Informatics Assoc..

[13]  Xiaodong Lin,et al.  Secure Regression on Distributed Databases , 2005 .

[14]  Christian Terwiesch,et al.  The Impact of Work Load on Service Time and Patient Safety: An Econometric Analysis of Hospital Operations , 2009, Manag. Sci..

[15]  Pascal Paillier,et al.  Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.

[16]  Eva Marie Stahl.  Emergency department overcrowding: Its evolution and effect on patient populations in Massachusetts , 2008 .

[17]  Michael B. Miller.  Linear Regression Analysis , 2013 .