Hustle, Director, Data Analytics and Engineering, Eti-Osa, Lagos State, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2022, 13(01), 832-846
Article DOI: 10.30574/wjarr.2022.13.1.0607
Received on 23 December 2021; revised on 26 January 2022; accepted on 29 January 2022
Due to the growth of e-commerce, new opportunities and threats have appeared in the electronic environment. This paper identifies the works that relate to the e-commerce transformation through data science and cybersecurity and highlights the importance of the machine learning algorithms. Data science can be used to make significant customer-related revelations, organize stocking, and form flexible pricing strategies in e-commerce businesses. At the same time, information security, backed up by machine learning, contributes to combating fraud, safe payment transactions, and the protection of information.
From the current practices and the examples involving Amazon, Alibaba, and others, this paper demonstrates how the application of the most popular machine learning algorithms, like supervised and unsupervised learning, reinforcement learning, as well as natural language processing, improves operations and security at once. In supervised learning, methods are trained to anticipate customers’ behavior and, at the same time, identify cases of fraud, whereas in the case of unsupervised learning, algorithms are designed to find patterns in the customer’s data that have not been identified earlier. RL enhances dynamic price determination as well as the recommendation system, while NLP enhances customer service and feedback analysis.
The paper also elaborates on the problem areas that are related to the machine learning application in e-commerce, such as data security, transparency of the machine learning model, and learning in real-life conditions. Understanding these dimensions within this paper will give a comprehensive analysis of how data science and cybersecurity, using machine learning approaches, are transforming e-commerce. Thus, the need for continuous development in these fields is underlined in order to maintain growth and protect e-commerce environments in the context of a world that progressively becomes digital.
Machine Learning; Data Science; Algorithms; Ecommerce; Cybersecurity
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TEMITOPE OLUWATOSIN FATUNMBI. Impact of data science and cybersecurity in e-commerce using machine learning techniques. World Journal of Advanced Research and Reviews, 2022, 13(1), 832-846. Article DOI: https://doi.org/10.30574/wjarr.2022.13.1.0607