Blockchain-Based Fake Product Identification System
Mrs. Sundari P
, Hameshwar S , Samson Durai S
In contemporary marketplaces, the integrity of the supply chain, customer safety, and brand trust are all seriously threatened by counterfeit goods. Conventional methods of product authentication, such barcodes and centralized databases, are extremely susceptible to manipulation, duplication, and illegal access. This study suggests a Blockchain-Based Fake Product Identification and Supply Chain Traceability System (BFPI-STS) that uses decentralized technology for transparent and safe product verification in order to address these issues. The suggested solution tracks ownership changes among various supply chain participants and records unchangeable product data using blockchain technology and smart contracts. Every product has a unique QR code that allows authorities and customers to verify it in real time. By removing the need for centralized control, the architecture improves trust, guarantees data integrity, and stops counterfeiting. To further expedite the procedures of product registration, tracking, and authentication, the system incorporates web-based interfaces and automated validation techniques. The suggested methodology provides an effective and scalable method of preventing counterfeit goods while enhancing the general transparency and dependability of the supply chain by fusing cryptographic security with decentralized architecture.
"Blockchain-Based Fake Product Identification System", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 4, page no.c434-c438, April-2026, Available :https://rjpn.org/JETNR/papers/JETNR2604321.pdf
Volume 4
Issue 4,
April-2026
Pages : c434-c438
Paper Reg. ID: JETNR_233975
Published Paper Id: JETNR2604321
Downloads: 00018
Research Area: Science and Technology
Country: Coimbatore, Tamil Nadu, India
ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: RJPN (IJPublication) Janvi Wave