Authors: Akanksha Upadhyaya; Vinod Shokeen; Garima Srivastava
Addresses: Amity Institute of Information Technology, Amity University, Noida, UP, India ' Amity School of Engineering, Amity University, Noida, UP, India ' Department of Computer Science, Dr. KNMIET, Modinagar, Ghaziabad, India
Abstract: Counterfeiting is an exhaustive problem smashing extensively, virtually as well as in reality, on each sector all around the world. In order to identify and classify fake and genuine banknote various techniques and models have been proposed and developed. This paper proposes an effective predictive model based on machine learning technique for authentication of banknotes, which can predicts with good accuracy that whether the given banknote is fake or genuine. The decision tree model is built using IBM SPSS tool. The performance measure of the model is done using gain charts and index charts and it is found that proposed decision tree model is good enough for prediction of banknote classification as fake or genuine.
Keywords: counterfeiting; fake and genuine banknotes; decision tree; banknote authentication; gain values; index values; machine learning; SPSS.
World Review of Entrepreneurship, Management and Sustainable Development, 2018 Vol.14 No.6, pp.683 - 693
Received: 14 Mar 2017
Accepted: 31 May 2017
Published online: 29 Jan 2019 *