Anti-Counterfeit Product Tracking System

Abstract

The rapid growth of e-commerce platforms has led to a rise in counterfeit products and fake websites. This has caused financial losses and decreased consumer trust. Manually spotting such fraud is difficult because of the high number of online transactions and the increasingly clever tactics used by counterfeiters. This work introduces an Anti-Counterfeit Product Tracking System that combines Artificial Intelligence and Blockchain technology to offer a dependable way to detect fraud and verify products. The system carries out dual verification by examining both website features and product-related details like pricing patterns. It evaluates suspicious signs, such as insecure protocols, unusual domain structures, and unrealistic product prices, using smart rules to produce a risk score between 0 and 100. Based on this score, the system labels inputs as Authentic, Suspicious, or Counterfeit, which helps in making clear decisions. To maintain security and transparency, all verification results are recorded using blockchain technology, which creates a secure and decentralized record. This method improves detection accuracy, allows for real-time verification, and lessens reliance on centralized systems, thereby boosting trust and security in online transactions.