Preventing Counterfeit Products using Cryptography, QR Code and Webservice

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.

Crime Detection using Data Mining Techniques

As crime rates keep spiraling each day, new challenges are faced by law enforcement agencies. They have to keep their on the lookout for any signs criminal activity. The law enforcement agencies should therefore be able to predict such increase or decrees or trends in crime. Such as theft, Killing. Crime that may occur in a particular area in a particular month, year, any timespan. Data mining is defined as a process of discovering hidden valuable knowledge by analyzing large amounts of data, which is stored in databases or data warehouse, using various data mining techniques such as machine learning, artificial intelligence, statistical. Many algorithms for data mining approach to help detect the crimes patterns. Data Collection, Data Preprocessing Phase, Data Filtering, Linier Regression. Wekasoft are used for collection of data analyzing. Visualization finally get results. The advantage of using this tool is that clustering will be performed automatically.