Blockchain and AI-Empowered Healthcare Insurance Fraud Detection: an Analysis, Architecture, and Future Prospects

被引:16
作者
Kapadiya, Khyati [1 ]
Patel, Usha [1 ]
Gupta, Rajesh [1 ]
Alshehri, Mohammad Dahman [2 ]
Tanwar, Sudeep [1 ]
Sharma, Gulshan [3 ]
Bokoro, Pitshou N. [3 ]
机构
[1] Nirma Univ, Inst Technol, Dept Comp Sci & Engn, Ahmadabad 382481, Gujarat, India
[2] Taif Univ, Coll Comp & Informat Technol, Dept Comp Sci, Taif 21944, Saudi Arabia
[3] Univ Johannesburg, Dept Elect Engn Technol, ZA-2006 Johannesburg, South Africa
关键词
Insurance; Security; Medical services; Blockchains; Costs; Encryption; Servers; Healthcare insurance; fraud detection; AI; blockchain; security; FRAMEWORK;
D O I
10.1109/ACCESS.2022.3194569
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nowadays, health insurance has become an essential part of people's lives as the number of health issues increases. Healthcare emergencies can be troublesome for people who can't afford huge expenses. Health insurance helps people cover healthcare services expenses in case of a medical emergency and provides financial backup against indebtedness risk. Health insurance and its several benefits can face many security, privacy, and fraud issues. For the past few years, fraud has been a sensitive issue in the health insurance domain as it incurs high losses for individuals, private firms, and governments. So, it is essential for national authorities and private firms to develop systems to detect fraudulent cases and payments. A high volume of health insurance data in electronic form is generated, which is highly sensitive and attracts malicious users. Motivated by these facts, we present a systematic survey for Artificial Intelligence (AI) and blockchain-enabled secure health insurance fraud detection in this paper. This paper presents a taxonomy of various security issues in health insurance. We proposed a blockchain and AI-based secure and intelligent system to detect health insurance fraud. Then, a case study related to health insurance fraud is presented. Finally, the open issues and research challenges in implementing the blockchain and an AI-empowered health insurance fraud detection system is presented.
引用
收藏
页码:79606 / 79627
页数:22
相关论文
共 88 条
  • [1] The benefits and threats of blockchain technology in healthcare: A scoping review
    Abu-elezz, Israa
    Hassan, Asma
    Nazeemudeen, Anjanarani
    Househ, Mowafa
    Abd-alrazaq, Alaa
    [J]. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2020, 142
  • [2] Blockchain Technology in Healthcare: A Systematic Review
    Agbo, Cornelius C.
    Mahmoud, Qusay H.
    Eklund, J. Mikael
    [J]. HEALTHCARE, 2019, 7 (02)
  • [3] Combating Abuse of Health Data in the Age of eHealth Exchange
    Ahmed, Musheer
    Ahamad, Mustaque
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI), 2014, : 109 - 118
  • [4] Network-based Active Defense for Securing Cloud-based Healthcare Data Processing Pipelines
    Akashe, Vaibhav
    Neupane, Roshan Lal
    Alarcon, Mauro Lemus
    Wang, Songjie
    Calyam, Prasad
    [J]. 30TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS (ICCCN 2021), 2021,
  • [5] Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019
    Al-Hashedi, Khaled Gubran
    Magalingam, Pritheega
    [J]. COMPUTER SCIENCE REVIEW, 2021, 40
  • [6] Phishing environments, techniques, and countermeasures: A survey
    Aleroud, Ahmed
    Zhou, Lina
    [J]. COMPUTERS & SECURITY, 2017, 68 : 160 - 196
  • [7] Alhasan Baker, 2021, 2021 International Conference on Information Technology (ICIT), P935, DOI 10.1109/ICIT52682.2021.9491664
  • [8] An Alternative Approach of Mitigating ARP Based Man-in-the-Middle Attack Using Client Site Bash Script
    Amin, A. A. M. Mazharul
    Mahamud, Md Sadad
    [J]. 2019 6TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ICEEE 2019), 2019, : 112 - 115
  • [9] Anbarasi M.S., 2017, P INT C INF COMM EMB, P1
  • [10] A review of the Ghana National Health Insurance Scheme claims database: possibilities and limits for drug utilization research
    Ankrah, Daniel
    Hallas, Jesper
    Odei, James
    Asenso-Boadi, Francis
    Dsane-Selby, Lydia
    Donneyong, Macarius
    [J]. BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2019, 124 (01) : 18 - 27