Recent Papers

The e-commerce industry has rapidly become an essential component of the global economy, transforming the way businesses and consumers interact. As digital transactions and online business continue to increase, so does the risk of cyberattacks, which are becoming more sophisticated and pervasive. These threatsranging from fraud and data breaches to denial-of-service (DDoS) attackspose significant challenges to e-commerce platforms, jeopardizing sensitive customer data and undermining the trust upon which these platforms depend. As a result, there is an urgent need for more effective cybersecurity solutions. Artificial Intelligence (AI), with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool to enhance security in the e-commerce domain.AI technologies, such as machine learning, deep learning, and predictive analytics, have the potential to revolutionize how cybersecurity threats are detected, mitigated, and prevented. These technologies enable real-time monitoring of transactions, anomaly detection, and automated responses to potential threats. For example, machine learning algorithms can learn from past attack patterns to predict and prevent future threats, while deep learning models can identify complex patterns in vast datasets, helping to recognize previously unseen attacks (Buczak & Guven, 2016; Zhou et al., 2020). Despite these promising advancements, challenges remain in the widespread adoption of AI-based solutions, particularly regarding scalability, integration with existing security frameworks, and ethical concerns related to data privacy and the transparency of AI decision-making processes.This literature review synthesizes the current body of research on AI applications in e-commerce cybersecurity, critically analyzing the strengths and limitations of these technologies. It provides a comprehensive overview of how AI can enhance threat detection, fraud prevention, and data protection in e-commerce environments. Furthermore, the paper highlights key trends and emerging research areas, including the need for adaptive AI systems that can evolve with increasingly complex cyber threats and the ethical considerations surrounding their deployment. Through this review, the paper aims to bridge existing knowledge gaps, providing a foundation for future research that explores more scalable and ethical AI solutions in e-commerce cybersecurity. Recent work by Yusuf, Oyetunji, Owoigbe, and Adesoga (2024) highlights Nigerias innovations in cloud cybersecurity, emphasizing practical, localized approaches to protecting digital spaces.

Copyright © 2025 KOLAWOLE VICTOR OWOIGBE. This is an open access article distributed under the Creative Commons Attribution License.