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author:

Liu, Ximeng (Liu, Ximeng.) [1] | Deng, Robert H. (Deng, Robert H..) [2] | Choo, Kim-Kwang Raymond (Choo, Kim-Kwang Raymond.) [3] | Yang, Yang (Yang, Yang.) [4]

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Abstract:

In this paper, we propose a privacy-preserving clinical decision support system using Naïve Bayesian (NB) classifier, hereafter referred to as Peneus, designed for the outsourced cloud computing environment. Peneus allows one to use patient health information to train the NB classifier privately, which can then be used to predict a patient's (undiagnosed) disease based on his/her symptoms in a single communication round. Specifically, we design secure Single Instruction Multiple Data (SIMD) integer circuits using the fully homomorphic encryption scheme, which can greatly increase the performance compared with the original secure integer circuit. Then, we present a privacy-preserving historical Personal Health Information (PHI) aggregation protocol to allow different PHI sources to be securely aggregated without the risk of compromising the privacy of individual data owner. Also, secure NB classifier is constructed to achieve secure disease prediction in the cloud without the help of an additional non-colluding computation server. We then demonstrate that Peneus achieves the goal of patient health status monitoring without privacy leakage to unauthorized parties, as well as the utility and the efficiency of Peneus using simulations and analysis. © 2008-2012 IEEE.

Keyword:

Classification (of information) Cloud computing Cryptography Decision support systems Diseases Health Health risks Niobium Servers

Community:

  • [ 1 ] [Liu, Ximeng]College of Mathematics and Computer Science, Fuzhou University, Fuzhou Shi, Fujian Sheng, China
  • [ 2 ] [Liu, Ximeng]School of Information Systems, Singapore Management University, Singapore, Singapore
  • [ 3 ] [Deng, Robert H.]School of Information Systems, Singapore Management University, Singapore, Singapore
  • [ 4 ] [Choo, Kim-Kwang Raymond]Department of Information Systems and Cyber Security, University of Texas at San Antonio, San Antonio; TX, United States
  • [ 5 ] [Yang, Yang]College of Mathematics and Computer Science, Fuzhou University, Fuzhou Shi, Fujian Sheng, China

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Source :

IEEE Transactions on Services Computing

Year: 2021

Issue: 1

Volume: 14

Page: 222-234

1 1 . 0 1 9

JCR@2021

5 . 5 0 0

JCR@2023

ESI HC Threshold:106

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 32

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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