Internet Banking(IB) frauds are relatively eaisier for hackers and attackers with malafide intentions and so the number of Internet banking frauds these days are overwhelming. E-commerce platforms and many other online shopping portals have included Internet Banking as a payment mode, increasing the risk for IB frauds. The primary intent of this research work is to improvise and develop a unique and new fraud identification technique for Internet Banking Transactions by analysing the past transaction and banking details of the customer and deduce the patterns in the nature of transactions done so as to be able to detect an anomalous transaction in future. Where IB account holders are grouped into different categories based on their transaction and internet banking activites. Then we make use of the sliding window protocol or strategy, to assimilate the transactions and activities done by the customers from different internet banking channels so that the patterns and similarities in the nature and type of the transactions belonging to different categories or groups can be inferred and extracted respectively.

Keywords : Internet Banking Transactions, Sliding Window Strategy, Concdept Drift