Big Data Analytics to Authenticate Bank Notes Using K-Means Clustering

Abstract

The main objective of this work is to use the given dataset (about the information of different variables of the different kind of bank notes that were analyzed) in such a way using an algorithm that will group the large values in the data as efficiently as possible into two groups of values then we can use those groups and make a model that can in future identify a forged note from the real ones. Forged banknotes are a major problem that the bank must tackle. It is very important to find a solution to stop this criminal action. One of the most important steps is to be able to identify which banknote is forged. There are many solutions to identify the forged banknote. In this manuscript, we propose one of the solutions to identify the forged banknotes using one of the machine learning methods called "K-Means Clustering".