IRO Journals
Journal of Artificial Intelligence and Capsule Networks

AUREL:AI-Driven Blockchain Platform for Authentic Product Verification and Trusted Recommendations

Open Access
Published: 10 July, 2026
Pages: 193-209
  • Sugantha Lakshmi R. , Sugantha Lakshmi R.
    Department of Computer Science and Engineering, Saranathan College of Engineering (Autonomous), Tiruchirappalli, India
    Department of Computer Science and Engineering, Saranathan College of Engineering (Autonomous), Tiruchirappalli, India
  • Abirami K. , Abirami K.
    Department of Computer Science and Engineering, Saranathan College of Engineering (Autonomous), Tiruchirappalli, India
    Department of Computer Science and Engineering, Saranathan College of Engineering (Autonomous), Tiruchirappalli, India
  • Harini P. , Harini P.
    Department of Computer Science and Engineering, Saranathan College of Engineering (Autonomous), Tiruchirappalli, India
    Department of Computer Science and Engineering, Saranathan College of Engineering (Autonomous), Tiruchirappalli, India
  • Jeya Keerthana M. Jeya Keerthana M.
    Department of Computer Science and Engineering, Saranathan College of Engineering (Autonomous), Tiruchirappalli, India
    Department of Computer Science and Engineering, Saranathan College of Engineering (Autonomous), Tiruchirappalli, India
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How to Cite

R., Sugantha Lakshmi, Abirami K., Harini P., and Jeya Keerthana M. 2026. “AUREL:AI-Driven Blockchain Platform for Authentic Product Verification and Trusted Recommendations”. Journal of Artificial Intelligence and Capsule Networks 8 (3): 193-209. https://doi.org/10.36548/jaicn.2026.3.003.
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Keywords

Product Authenticity Verification
Fake Detection
Computer Vision
Blockchain
Behavioral Scan Analytics
Recommendation System

Abstract

The widespread use of fake cosmetic and personal care products has become a threat to consumer safety and product authenticity. Traditional verification methods such as QR codes, holograms, and centralized database are vulnerable to duplication and manipulation. To overcome these issues, this paper proposes AUREL, an AI-enabled blockchain platform for authentic product verification and recommendations. The proposed AUREL framework consists of product registration with blockchain, AI-based product visual verification, behavioral scan analytics, and recommendation service. In the developed application framework, first, manufacturers register the product information with a hash code generated by cryptographic technique. Second, consumers scan QR codes and take pictures of packages of the products through a mobile application for verification. Third, the system validates the blockchain and analyses the authenticity of the product to identify the unusual verification activities. A decision fusion algorithm is used to combine the outputs of each verification layer to classify products as genuine, suspicious, or fake. Finally, when fake products are found, the recommendation system suggests verified alternative products to the consumers. The proposed solution has been experimentally evaluated with a product verification success rate of 98.4%.

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