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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Akhil Raj Gaius Yallamelli & Vijaykumar Mamidala & Mohanarangan Veerappermal Devarajan & Rama Krishna Mani Kanta Yalla & Thirusubramanian Ganesan & Aceng Sambas, 2024. "Hybridized Multi-Special Decision Finding with Anti-Theft Probabilistic Method in the Improvement of Cloud-Based E-Commerce," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-26, December.
  • Handle: RePEc:wsi:ijitmx:v:21:y:2024:i:08:n:s0219877024400030
    DOI: 10.1142/S0219877024400030
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