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Opportunities, Challenges, and Future Directions of Strategic Innovations of AI and ML for E-Commerce Data Security
Abstract
In today's digital landscape, E-commerce has become a dominant force in global commerce. As E-commerce platforms collect vast amounts of sensitive customer information, safeguarding this data against cyber threats is paramount. Integrating machine learning (ML) and artificial intelligence (AI) technology has become a viable strategy for improving e-commerce data security in recent years. This paper presents the opportunities, challenges, and future directions associated with the strategic application of AI and ML in bolstering E-commerce data security. The future directions of strategic innovations in AI and ML for E-commerce data security are multifaceted. One key area of focus involves the development of AI-driven adaptive security systems capable of autonomously adapting to emerging threats. Finally, while significant opportunities exist to leverage these technologies for threat detection and mitigation, overcoming associated challenges and pursuing innovative approaches will be essential for safeguarding the integrity and confidentiality of E-commerce transactions.
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