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Conference Paper Detecting Counterfeit Products Using Supply Chain Event Mining
Cited 6 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Ho Sung Lee, Hyo Chan Bang
Issue Date
2013-01
Citation
International Conference on Advanced Communication Technology (ICACT) 2013, pp.744-748
Publisher
IEEE
Language
English
Type
Conference Paper
Abstract
Counterfeiting is a growing problem all over the world, threatening the health of consumers and lead to financial losses for legally run business. By detecting counterfeit products before they are distributed to the end-users, the problem can be prevented. In this study, we propose an alternative frequent pattern mining algorithm to discover licit supply chain patterns from trace records and a classification algorithm to distinguish counterfeit products with these licit supply chain patterns. The presented algorithms are studied with computer simulations that model the flow of genuine and counterfeit products in a comprehensive supply chain. The results suggest that these algorithms could be used to automatically detect suspicious products. © 2013 GIRI.
KSP Keywords
Classification algorithm, Computer simulation(MC and MD), Counterfeit products, End users, Event mining, Financial losses, Frequent Pattern Mining, Pattern mining algorithm, supply chain