Hybridized Multi-Special Decision Finding with Anti-Theft Probabilistic Method in the Improvement of Cloud-Based E-Commerce

Akhil Raj Gaius Yallamelli, Vijaykumar Mamidala (), Mohanarangan Veerappermal Devarajan (), Rama Krishna Mani Kanta Yalla (), Thirusubramanian Ganesan () and Aceng Sambas
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Akhil Raj Gaius Yallamelli: Amazon Web Services Inc., Seattle, USA
Vijaykumar Mamidala: ��Conga (Apttus), Broomfield, CO, USA
Mohanarangan Veerappermal Devarajan: ��Ernst & Young (EY), Sacramento, USA
Rama Krishna Mani Kanta Yalla: Amazon Web Services Inc., Seattle, USA
Thirusubramanian Ganesan: �Cognizant Technology Solutions, Texas, USA
Aceng Sambas: �Faculty of Informatics and Computing, Universiti Sultan, Zainal Abidin, Campus Besut, 22200 Terengganu, Malaysia∥Department of Mechanical Engineering, Universitas Muhammadiyah, Tasikmalaya, Tamansari Gobras, 46196 Tasikmalaya, Indonesia

International Journal of Innovation and Technology Management (IJITM), 2024, vol. 21, issue 08, 1-26

Abstract: In addition to dealing with the dispute between the e-commerce activities of companies and the lack of supplies, the companies had settled, by applying a highly developed cloud technology framework, the difficulties of lack of resources, workforce and necessary technology in e-commerce activities. E-commerce utilizing cloud-based financial instruments is becoming a common strategy for the rise of international growth over the years. Nevertheless, the presence of fake goods on the site endangered the advantages of all investors. Therefore, this paper suggests a Hybridized Multi-special Decision finding with the Anti-Theft Probabilistic (HMDAP) method for making the improvement of the cloud-based model, and it is trained to find fake goods. A multi-special decision finding is used to address the issues and the lack of e-commerce facilities by creating a programming environment for e-commerce provided by the cloud computing system. The Anti-Theft Probabilistic method is used to track fake goods and use the Carlo method to predict possible stolen data in e-commerce. HMDAP enables businesses to reduce expenses through the successful delivery of e-commerce activities and provides assumptions of unsafe data in e-commerce.

Keywords: E-Commerce; cloud-based method; fake goods; business (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219877024400030

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