Fake Product Identification System Using Blockchain

Abstract

Counterfeits are some of the common issues facing this day’s world market, from electronics to pharmaceuticals. Such Counterfeit products damage brands and pose a significant danger to consumer health as well. The traditional methods adopted for identifying counterfeit products are inefficient and prone to tampering. Blockchain technology promises an ideal solution for this challenge. With blockchain as decentralized, open, and tamper-proof technology, the supply chain will be traceable from where it originated to reach its final usage in the user’s hands. For every single product, allocate a unique digital identity, so the journey the product has taken to reach the marketplace will be recorded in the blockchain; therefore, one can easily track the authenticity with the help of both consumers and businesses. In this review, we discuss the likelihood of blockchain technology being an avenue for identifying fake products, not only enhancing trust and transparency but also lowering the level of counterfeit goods in the market. Various Blockchain-based approaches have been discussed to reveal current challenges in implementation and potential future prospects for comprehensive adoption.

Introduction

Counterfeit products pose serious financial and safety risks across many industries, including luxury goods, electronics, pharmaceuticals, and food. Traditional anti-counterfeiting methods like security labels and RFID tags are increasingly ineffective due to sophisticated counterfeiters. Blockchain technology, known for its transparency, immutability, and decentralization, offers a promising solution for counterfeit detection.

This paper proposes a system combining blockchain with artificial intelligence and machine learning to detect fake products. The system registers product details on a blockchain, generates unique QR codes for each product, and allows consumers to verify authenticity by scanning these codes. The blockchain stores product data and transaction history securely, making it nearly impossible to tamper with or forge product information.

A literature survey highlights previous blockchain-based anti-counterfeiting solutions applied in supply chains, online marketplaces, and luxury goods, often integrating IoT, NFC, or machine learning technologies.

The system architecture involves manufacturers registering products and generating QR codes linked to blockchain hashes. Consumers scan these QR codes to confirm product legitimacy. The project utilizes Ethereum blockchain, smart contracts, and cryptographic hashing (SHA-256) for secure, decentralized verification.

Experimental results demonstrate that authentic products show detailed blockchain-verified data upon scanning, while counterfeit items do not, enabling effective real-time authentication.

Conclusion

The adding number of products available online is the primary reasons why fake products are growing fleetly.thus, there\'s a strong need to find the fake product, and the blockchain technology is used to descry similar products.Alternate information is decoded in a QR law.later, druggies or guests overlook the QR law and they can find the fake product.In blockchain technology, digital information about the product can be stored in the form of blocks thus, in this paper we parried the system and the result to combat the malpractices of counterfeiting of the products, and suggested the system which is beneficial for end stoner to descry whether the product is fake or not by checking the throughout history of the product in force chain.End stoner can overlook QR law assigned this means that it can trace a product and can get all the information put up throughout theforce chain.Counterfeiting products is one of the long terms issued face in the request and needed an effective and safe system to identify and help the issue.This blockchain grounded discovery of fake product system offers tamper proofing with robotization as it detects and prevents the selling of fake products.The use of blockchain technology and the capacity of smart contracts give security in this system by automating through the invariability and safety offered by the technology.further these approaches needed exploration to determine their scalability and feasibility in the real world.

References

[1] A. M. Khan, S. S. Khurram, A. Alamri, and M. A. Hossain, \"BlockChain-based secure and trustworthy supply chain management for counterfeit detection,\" Computers & Electrical Engineering, vol. 91, pp. 106966, 2021. [2] N. A. Afzal, M. A. Imran, F. M. Wajid, and M. A. B. Baig, \"Blockchain-based supply chain management for counterfeit detection,\" in Proceedings of the 2021 IEEE 17th International Conference on Emerging Technologies (ICET), pp. 1-6, 2021. [3] T. Zhang, X. Liu, and F. Lu, \"Fake product detection system based on blockchain and machine learning,\" in Proceedings of the 2021 IEEE 8th International Conference on Industrial Engineering and Applications (ICIEA), pp. 241-245, 2021. [4] Z. Zhang, Y. Liu, X. Liu, and M. Guo, \"A blockchain-based framework for detecting counterfeit products in supply chain,\" IEEE Access, vol. 8, pp. 196464-196476, 2020. [5] K. Ali, M. M. Hassan, and M. M. Rahman, \"Blockchain-based counterfeit system using anti product lifecycle,\" in Proceedings of the 2020 IEEE 2nd International Conference on Computing, Communication and Security (ICCCS), pp. 1-6, 2020 [6] ASPA, The state of counterfeiting in india 2021, https : / / www.aspaglobal.com / pre_upload / nation / 1623216858-4730baa0efdb83aba174859af0a3a6a5- Report % 20The % 20State % 20of % 20Counterfeiting % 20in % 20India % 202021.pdf (2021) [7] F. Casino, T.K. Dasaklis, C. Patsakis, Telematics Informatics 36, 55 (2019). [8] M. Peck, IEEE Spectrum 54, 26 (2017). [9] S. Idrees, M. Nowostawski, R. Jameel, A. Mourya, Electronics 10, 951 (2021). [10] J. Ma, S.Y. Lin, X. Chen, H.M. Sun, Y.C. Chen, H. Wang, IEEE Access 8, 77642 (2020). [11] M.J.L.I.N.M. J.M. Bohli, N. Gruschka, IEEE 10, 9 (2013).

Copyright

Copyright © 2025 Prajakta Bhere, Apeksha Bhoir, Roshani Bhoir, Priyanka Dhole, Naresh Shende. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.