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  Evidential Modeling for Telemedicine Continual Security  
  Authors : Sofienne Mansouri, Bel G Raggad
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Telemedicine has not advanced at the same pace as IT and its own medical technologies. The long-awaited progress has been hindered aggressively by security risks that came with innovative information and communication technologies. One major technological factor to blame for this tardiness in telemedicine is its information security that lead to patients and doctors attrition and hence system infeasibility. Given the great deal of uncertainties and ambiguities in the telemedicine environment, Bayesian reasoning does not offer a sound approach to tackle all the security problems menacing telemedicine. For this article proposes an evidential reasoning model to manage risks due to security uncertainties and ambiguities characterizing most telemedicine environments. Dempster and Shafer Theory is used to process security management evidence for the purpose to forecast the overall security risks associated with the continual feasibility of a telemedicine system. This article also provides a numerical example to demonstrate the working of the proposed evidential reasoning model.

 

Published In : IJCSN Journal Volume 6, Issue 5

Date of Publication : October2017

Pages : 559-564

Figures :04

Tables : 02

 

Sofienne Mansouri : U of Tunis El-Manar, ISTMT, Lab of Biophysics and Medical Technologies, Tunisia.

Bel G Raggad : Seidenberg School of CS & IS, Pace U, New York, USA.

 

Telemedicine, Dempster and Shafer theory, evidential reasoning, Belief functions, security risk.

The article looked into the telemedicine tardiness in following current advances in information and telecommunication technologies and proposed an evidential reasoning model to tackle its security problems believed to be one of the major hinders of telemedicine progress. Given the great deal of uncertainties and ambiguities in the telemedicine environment, Bayesian reasoning does not offer a sound approach to tackle all those security problems menacing telemedicine. We proposed an evidential reasoning model to manage risks due to security uncertainties and ambiguities characterizing most telemedicine environments.

 

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