Paper Title
SECURING E-COMMERCE: AI-POWERED FRAUD DETECTION AND PREVENTION
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Authors
Keywords
E-commerce, artificial intelligence, algorithm
Abstract
This abstract presents an AI-driven approach to fortify fraud detection and prevention mechanisms within e-commerce websites. In response to the escalating threat of fraudulent activities, this system harnesses the capabilities of Artificial Intelligence (AI) to proactively identify and mitigate risks. By analyzing vast datasets in real-time, AI algorithms adeptly discern patterns indicative of fraudulent behavior, enabling swift intervention to safeguard the integrity of transactions. Leveraging machine learning techniques, the system continually refines its understanding of evolving fraud tactics, adapting to new threats with precision and agility. Behavioral analysis forms a cornerstone of this framework, scrutinizing user interactions and transactional patterns to detect anomalies and flag potential fraud. Through advanced data visualization tools, stakeholders gain actionable insights into emerging trends and suspicious activities, empowering informed decision-making. By integrating AI-powered fraud prevention measures, e-commerce platforms bolster their security posture, fostering trust and confidence among users while mitigating financial losses. This innovative approach signifies a paradigm shift in combating fraud within the digital marketplace, underscoring the transformative potential of AI in safeguarding the interests of businesses and consumers alike.
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How To Cite (APA)
MANASA A S & Ashish L (March-2024). SECURING E-COMMERCE: AI-POWERED FRAUD DETECTION AND PREVENTION . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), f28-f33. https://ijnrd.org/papers/IJNRD2403504.pdf
Issue
Volume 9 Issue 3, March-2024
Pages : f28-f33
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Paper Reg. ID: IJNRD_216531
Published Paper Id: IJNRD2403504
Downloads: 000122253
Research Area: Master of Computer ApplicationÂ
Author Type: Indian Author
Country: Thrissur, Kerala, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2403504.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403504
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