International Journal on Science and Technology

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AI-Powered Fake Product Detection System

Author(s) Kanak Verma, Priyanshi Bilgaiya, Rishika Bhatia, Shriyanshi Bilgaiya, Prof. Sonali Rathore
Country India
Abstract In Today’s Generation, Counterfeit products are a growing global issue, affecting consumers, businesses, and economies. The emergence of artificial intelligence (AI) has provided innovative solutions to detect and prevent fake products. This research paper explores AI-based approaches to identifying counterfeit goods, including image recognition, natural language processing (NLP), blockchain integration, and machine learning techniques. The study also discusses the implementation and effectiveness of these tools in real-world scenarios.
Counterfeit products pose a significant challenge across various industries, including pharmaceuticals, electronics, fashion, and luxury goods. Traditional methods of counterfeit detection, such as manual inspection and holograms, are increasingly ineffective against sophisticated counterfeiting techniques. This paper explores the use of Artificial Intelligence (AI) tools for detecting fake products through image recognition, blockchain authentication, natural language processing (NLP), and machine learning algorithms. AI-powered image recognition can identify discrepancies in product packaging, barcodes, and QR codes, while blockchain technology ensures product traceability and authenticity. NLP techniques analyze consumer reviews and seller credibility to identify fraudulent products in e-commerce platforms.
Additionally, deep learning models, such as Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs), enhance counterfeit detection by learning subtle product variations. This study highlights the effectiveness of AI-driven approaches in combating counterfeit goods and emphasizes the need for continuous advancements in AI-powered authentication systems.
Keywords Counterfeit Products, Artificial Intelligence, Logos, Technotard
Field Engineering
Published In Volume 16, Issue 1, January-March 2025
Published On 2025-03-27
Cite This AI-Powered Fake Product Detection System - Kanak Verma, Priyanshi Bilgaiya, Rishika Bhatia, Shriyanshi Bilgaiya, Prof. Sonali Rathore - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.3029
DOI https://doi.org/10.71097/IJSAT.v16.i1.3029
Short DOI https://doi.org/g892cp
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