B. Girimurugan, Manikanta Kuchi, Mani Sriram.T, V. Kumaresan, Suparna Gopi Nair, Nur Kholifah
With the continuous rise of e-commerceandits integration intomany aspects of daily life, advanced methods of protection have grown dearer. AI and machine learning technologies are on the rise, allowing businesses in the e-commerce field to improve their security protocols and processes for securing customer and sensitive corporate data. Over the next decade or so, AI and machine learning will change the face of e-commerce security in multiple positive ways. Also, AI-driven chatbots are one of the trends in e-commerce security. E-commerce transactions can also benefit from risk assessment and mitigation, thanks to the availability of machine learning algorithms. Through analysis of the data and history of transactions in the past, it is possible to detect risks and demand more authentication for high-risk types of transactions. This chapter covers the technologies analysis on large amount of data to identify patterns and anomalies, enabling real-time fraud detection and enhanced user authentication. Emerging trends include the use of AI-driven chatbots for se-cure customer interactions, ML algorithms for personalized security measures, and predictive analytics to anticipate and mitigate potential threats. Together, AI and ML are setting new standards for safeguarding e-commerce platforms, ensuring a safer shopping experience for consumers. © 2024 by IGI Global. All rights reserved.
Koneru Lakshmaiah Education Foundation (Deemed), India; Knowledge Institute of Technology, India; KPR College of Arts, Science and Research, India; Yogyakarta State University, Indonesia
