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AI and Machine Learning Applications for Preserving Privacy and Data Leakage of E-Commerce Data
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Author(s): Jatin Arora (Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India), Gaganpreet Kaur (Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India), Monika Sethi (Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India)and Saravjeet Singh (Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India)
Copyright: 2025
Pages: 20
Source title:
Strategic Innovations of AI and ML for E-Commerce Data Security
Source Author(s)/Editor(s): Gaganpreet Kaur (Chitkara University, India), Jatin Arora (Chitkara University, India), Vishal Jain (Sharda University, Greater Noida, India)and Asadullah Shaikh (Najran University, Saudi Arabia)
DOI: 10.4018/979-8-3693-5718-7.ch003
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Abstract
The e-commerce industry has been expanding at an exponential rate, evolving and adapting even during times of national lockdowns and worldwide pandemics. In a relatively short period of time, the Indian e-commerce ecosystem has grown to be vital to both the country's internet users and economy. The e-commerce industry has also seen a rise in cyberattacks. These attacks frequently result in data leaks that compromise data integrity, violate customers' rights and privacy, and foster mistrust between online retailers and their clientele. The roots of e-commerce security problems are highlighted in this paper, along with the potential benefits of several cutting-edge technologies including machine learning (ML) and artificial intelligence (AI) in reducing security risks. To increase e-commerce security, the study suggested a number of methods, including as data encryption, secure payment gateways, multi-factor authentication (MFA), regular software updates and patches, user privacy policies, and compliance.
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