An augmented AI-based hybrid fraud detection framework for invoicing platforms-Reference-Cited by-同舟云学术

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An augmented AI-based hybrid fraud detection framework for invoicing platforms

Published:2024-01 Issue:2 Volume:54 Page:1297-1310
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Wahid Dewan F.^ORCID,Hassini Elkafi

Funder

Natural Sciences and Engineering Research Council of Canada

Mitacs

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10489-023-05223-x.pdf

Reference75 articles.

1. Agnisarman S, Lopes S, Madathil KC, Piratla K, Gramopadhye A (2019) A survey of automation-enabled human-in-the-loop systems for infrastructure visual inspection. Autom Constr 97:52–76

2. Al-Hashedi KG, Magalingam P (2021) Financial fraud detection applying data mining techniques: a comprehensive review from 2009 to 2019. Comput Sci Rev 40:100402

3. Al-Mohair HK, Saleh JM, Suandi SA (2015) Hybrid human skin detection using neural network and k-means clustering technique. Appl Soft Comput 33:337–347

4. Amazon (2021) Cyber defence in the age of AI, smart societies and augmented humanity. https://rb.gy/ruvuj5. Accessed 23 Feb 2023

5. Asatiani A, Apte U, Penttinen E, Rönkkö M, Saarinen T (2019) Impact of accounting process characteristics on accounting outsourcing comparison of users and non-users of cloud-based accounting information systems. Int J Account Inf Syst 34:100419

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2. Enhancing Cybersecurity Through Advanced Fraud and Anomaly Detection Techniques: A Systematic Review;2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG);2024-04-02

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