Secure Morph: A Secure Login System using visual Puzzle Authentication
Keywords
Abstract
In today's digital world, securing online identities is very important. Password-based authentication systems are increasingly vulnerable to phishing, brute-force, and social engineering attacks. To address these issues, this paper introduces "Secure Morph," a secure login system using visual puzzle-based authentication. Users register with their email ID and multiple personal images. During login, one of these uploaded images is randomly selected and displayed alongside AI-generated visually similar decoy images. Users are need to identify the correct image within three (3) attempts. Upon successful selection, a puzzle based on that image must be solved within a time limit. Failure to authenticate within the given constraints results in temporary account lockout. This multi-factor, cognitive-image-based authentication approach enhances resistance to automated attacks while preserving user experience. Secure Morph leverages HTML, CSS, JavaScript for frontend, Python Flask for backend, and utilizes image generation APIs from Hugging Face and Stability AI.
Copyright & License
Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this Article
Ms. Kolli Karishma, Dr. Suvarna Kumar Gogula (2025). Secure Morph: A Secure Login System using visual Puzzle Authentication. International Journal of Technology & Emerging Research (IJTER), 1(2), 22-30
BibTeX
@article{ijter2025212506300717,
author = {Ms. Kolli Karishma and Dr. Suvarna Kumar Gogula},
title = {Secure Morph: A Secure Login System using visual Puzzle Authentication},
journal = {International Journal of Technology & Emerging Research },
year = {2025},
volume = {1},
number = {2},
pages = {22-30},
issn = {3068-109X},
url = {https://www.ijter.org/article/212506300717/secure-morph-a-secure-login-system-using-visual-puzzle-authentication},
abstract = {In today's digital world, securing online identities is very important. Password-based authentication systems are increasingly vulnerable to phishing, brute-force, and social engineering attacks. To address these issues, this paper introduces "Secure Morph," a secure login system using visual puzzle-based authentication. Users register with their email ID and multiple personal images. During login, one of these uploaded images is randomly selected and displayed alongside AI-generated visually similar decoy images. Users are need to identify the correct image within three (3) attempts. Upon successful selection, a puzzle based on that image must be solved within a time limit. Failure to authenticate within the given constraints results in temporary account lockout. This multi-factor, cognitive-image-based authentication approach enhances resistance to automated attacks while preserving user experience. Secure Morph leverages HTML, CSS, JavaScript for frontend, Python Flask for backend, and utilizes image generation APIs from Hugging Face and Stability AI.},
keywords = {Visual puzzle authentication, AI image generation, Cyber security, Human cognitive skills},
month = {Jun},
}