Designing Counterfeit Technique For The Enhancement of Data Authenticity

Abstract

Data Authentication is the process of confirming and validating the data with correct classification as genuine and forged entity. Due to rise in counterfeiting, Banknote authentication has become one of the significant areas of data authentication. Counterfeiting is an exact imitation of a valuable entity with an intention to cheat. Forgery in the form of counterfeiting has become a profound issue smacking massively on each sphere of the world. Counterfeiting in terms of forged currency constitutes a significant menace to national wealth, nation s socio-economy, financial Institutions and consumers, globally. Currency counterfeiting is a crime under the Criminal law, Section 489 A, B, C, D,E of IPC, and if counterfeit notes are disseminated for funding incendiary activities within state or extraterritorial then a case shall be registered under Unlawful Activities Prevention Act (UAPA) 2008 revision of UAPA 1967. Therefore, in order to identify and distinguish unlawful entity, an effective predictive-classification model is proposed, which can predict the classification of counterfeit and genuine banknotes. The research is primarily focused on to designing of classification model for differentiating counterfeited banknotes and genuine banknotes. Designing of banknote authentication model leads to other preliminary study so as to realize the exact scenario and need of the current study.Designing of banknote authentication model leads to other preliminary study so as to realize the exact scenario and need of the current study.The entire research has been conducted using IBM SPSS 21, RStudio and IBM AMOS 20. Therefore, the research provides a thorough analysis, causes and an effective predictive-classification model for banknote authentication.