An Adaptive Decision-Making Approach for Better Selection of Blockchain Platform for Health Insurance Frauds Detection with Smart Contracts: Development and Performance Evaluation

Rima Kaafarani, Leila Ismail, Oussama Zahwe

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)

Abstract

Blockchain technology has piqued the interest of businesses of all types, while consistently improving and adapting to business requirements. Several blockchain platforms have emerged, making it challenging to select a suitable one for a specific type of business. This paper presents a classification of over one hundred blockchain platforms. We develop smart contracts for detecting healthcare insurance frauds using the top two blockchain platforms selected based on our proposed decision-making map approach which selects the top suitable platforms for healthcare insurance frauds detection application. Our classification shows that the largest percentage of platforms can be used for all types of application domains, the second biggest percentage for financial services, and a small number is to develop applications in specific domains. Our decision-making map and performance evaluations reveal that Hyperledger Fabric surpassed Neo in all metrics for detecting healthcare insurance frauds.

Original languageEnglish
Pages (from-to)470-477
Number of pages8
JournalProcedia Computer Science
Volume220
DOIs
Publication statusPublished - 2023
Event14th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2023 and The 6th International Conference on Emerging Data and Industry 4.0, EDI40 2023 - Leuven, Belgium
Duration: Mar 15 2023Mar 17 2023

Keywords

  • Blockchain
  • Decision-Map
  • Health Insurance Frauds Detection
  • Hyperledger Fabric
  • Neo
  • Smart Contract
  • Smart Healthcare

ASJC Scopus subject areas

  • General Computer Science

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