Abstract
Abstract The main issue in the present situation is how to secure the data in the online digital world. Most of the online accounts are protected using text passwords, OTP, and biometric systems. But they have their own limitations. Therefore to increase the security in a different direction, three different approaches are proposed. And they are Convolutional Neural Network, Levenshtein Distance, and Sequence Matcher. These three are used to implement the FreeHand Sketch-based Authenticated Security System to check the image password similarity for authentication purposes. These three proposed methodologies commonly request the user to draw the image password for registration and if all the credentials are satisfied then the image password will be stored in the system database. The user gets login with his/her image password if it got matched with the registered image password. The accurate results of each proposed approach are compared with the recall and precision metrics.
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