Natural language processing and stable diffusion model based graphical authentication using passphrase

Abstract

Graphical passwords or passphrases (GPs) are examined as reliable authentication system over text-based passphrases. Several obtainable applications utilize GPs and image-based authentication schemes. Even though, these authentication methods experience an issue of managing image or pictorial data. Here, Natural Language Processing (NLP)+Stable Diffusion (SD)_graphical authentication is presented for graphical authentication using passphrase. The passphrase, removing stop words, spell check, similarity check, stemming and lemmatization, label encoder, positional embedding and encryption are the steps carried out in registration phase whereas decryption Advanced Encryption Standard (AES), sentence generation, image set generation and grid module are conducted in verification phase. Initially, passphrase is considered and then, stop words are removed from it. Thereafter, spell check as well as similarity check are done and after these processes stemming and lemmatization is performed. In label encoder, label is generated for individual word in passphrase. Afterwards, positional embedding is done and lastly, encryption is conducted in registration phase. In verification phase, encrypted passphrase is decrypted, sentence is generated utilizing Generative Pre-trained Transformer (GPT), image set is generated by SD model and finally, image grid module is accomplished. Moreover, NLP+SD_graphical authentication achieved minimum attack detection, login failure, login time about 0.598, 0.191, 14.175sec and maximum memorability about 0.932.