Development of a Differential Evolution-based Fuzzy Cognitive Maps for Data Breach in Health-care Sector Fuzzy Cognitive Maps for Data Breach

Desmond Eseoghene Ighravwe, Daniel Mashao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

The last three decades have witnessed an increased concern in data breaches. This problem is more pronounced in patients' health information (PHI) management. Previous researchers have reported the need to address this problem from a multi-criteria perspective; however, there is sparse information on how to use fuzzy logic to integrated PHI data breach criteria. This article, therefore, presents a fuzzy-based model, which is a fuzzy cognitive map, for a data breach in health-centres using organizational and human criteria. This model combines fuzzy logic, decision-makers' opinions and cognitive maps method. Decision-makers' opinions were analysis from optimistic, pessimistic and most likely perspectives. The performance of this model has evaluated three FCM data breach forecasting scenarios. And the results obtained showed that the model predicts PHI data breach under different multi-criteria conditions. This article has been able to shed insights into the application of a fuzzy cognitive map for data breach problem in health-care centres.

Original languageEnglish
Title of host publicationIEEE AFRICON 2019
Subtitle of host publicationPowering Africa's Sustainable Energy for All Agenda: The Role of ICT and Engineering, AFRICON 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728132891
DOIs
Publication statusPublished - Sept 2019
Event2019 IEEE AFRICON, AFRICON 2019 - Accra, Ghana
Duration: 25 Sept 201927 Sept 2019

Publication series

NameIEEE AFRICON Conference
Volume2019-September
ISSN (Print)2153-0025
ISSN (Electronic)2153-0033

Conference

Conference2019 IEEE AFRICON, AFRICON 2019
Country/TerritoryGhana
CityAccra
Period25/09/1927/09/19

Keywords

  • Fuzzy cognitive maps
  • data management
  • differential evolution
  • health-care sector

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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