Application of LSTM for Differentiating Real and Fake Bank Names from Provided Uniform Resource Locator

The most crucial element of our everyday activities is security. As we progress in life, we must constantly keep our financial situation in mind. A phony online or offline transfer could result in an inevitable loss in our existence. To prevent this, we must confirm the correct bank name from uniform resource locator (URL) prior to making any changes. Every action taken with the bank's name assistance depends on its proper URL. It is necessary to identify the correct URL before any transaction or access to bank website. There are various methods which can be applied to identify correct bank URL, Long Short-Term Memory (LSTM), a supervised deep learning technique can be efficient method to identify bank URL. The main component of the LSTM algorithm is memory, which allows users to commit genuine bank names to memory. This helps users to confirm the authenticity of the bank name before making any website utilization. In the implemented system, URL identification is done through feature extraction, data preprocessing on collected data set for training and prediction purpose. Overall results shows that LSTM can provide approximately 94 % accuracy to detect the fake bank name from URL.