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Preventing Counterfeit Products using Cryptography, QR Code and Webservice

Authors: Cheman Shaik;

Preventing Counterfeit Products using Cryptography, QR Code and Webservice

Abstract

Counterfeit production is a threat for every genuine business causing damage to their brand image and stealing their revenues. The aim of this paper is topresenta novel method to prevent counterfeit products using cryptography, QR code and webservice. The method requires that every original product manufacturer obtain a cryptographic key pair, securely store their private key and publish their public key on their website as a QR code. The product manufacturer needs to print a unique item code on their product packs and provide inside the pack a QR code encoding the ciphertext generated by encrypting the item code with their private key. For product verification by buyers, the manufacture is required to provide a QR code scanning app for download on their website, Google Play Store or iPhone App Store. The scanning app should have additional cryptographic functionality to decrypt ciphertext of the item code encoded in the QR code. The manufacturer also needs to launch a simple webservice on his hosting server to accept requests from the mobile app and verify the item code and buyer’s name in its database. Technicalimplementation and the verification process are described in detail through figures and flowchart. The method can be implemented even by small manufacturers with nominal cost by obtaining a key pair and creating a scanning app and webservices. We have also tested the method with an actual software code written for cryptographic operations using the Java cryptography Extension and QR code operations using Google Zxing libraries.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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19
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5
10
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