Securing Local E-Commerce Businesses Against Cyber Attacks Using Deep Learning Algorithms

Local e-commerce businesses face critical cybersecurity threats such as fake reviews, phishing attacks, and brute-force logins. This paper introduces RealCheck, a deep learning-driven cybersecurity framework integrating NLP, Support Vector Machines (SVM), and CAPTCHA systems to detect fraudulent reviews, block malicious URLs, and prevent unauthorized access. Evaluated against ISO 25010:2011 standards, RealCheck achieved high accuracy and reliability, demonstrating its potential to safeguard small-scale e-commerce platforms. By addressing these challenges through an AI-driven, multi-layered approach, this work offers a practical and scalable solution tailored to local e-commerce needs.

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Publication Details

Published
2024-12-27
DOI
https://doi.org/10.1109/iceet65156.2024.10913799
Citations
1
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.35
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Securing Local E-Commerce Businesses Against Cyber Attacks Using Deep Learning Algorithms

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1 citations
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Securing Local E-Commerce Businesses Against Cyber Attacks Using Deep Learning Algorithms

Vivien A. Agustin, Criselle J. Centeno, M. Guzmán, Marilou B. Mangrobang, Antoinne Matthew G. Albao, Daryl Nicole C. Jayme
article en
1 citations

Abstract

Local e-commerce businesses face critical cybersecurity threats such as fake reviews, phishing attacks, and brute-force logins. This paper introduces RealCheck, a deep learning-driven cybersecurity framework integrating NLP, Support Vector Machines (SVM), and CAPTCHA systems to detect fraudulent reviews, block malicious URLs, and prevent unauthorized access. Evaluated against ISO 25010:2011 standards, RealCheck achieved high accuracy and reliability, demonstrating its potential to safeguard small-scale e-commerce platforms. By addressing these challenges through an AI-driven, multi-layered approach, this work offers a practical and scalable solution tailored to local e-commerce needs.

University of the City of Manila (PH)
Openalex Percentile: Top 33%
Network Security and Intrusion Detection
0.35
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