Reinventing Authentication through User-Centric Two-Factor Security and Personalized Image Verification

J Sivarani; D Lashya Kumari; A Jyothsna; S K Mohammed Khaif; I Hithaishi

doi:10.5281/zenodo.18683037

Authors

J Sivarani Department of CSE (IoT and Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.
D Lashya Kumari Department of CSE (IoT and Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.
A Jyothsna Department of CSE (IoT and Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.
S K Mohammed Khaif Department of CSE (IoT and Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.
I Hithaishi Department of CSE (IoT and Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.

DOI:

https://doi.org/10.5281/zenodo.18683037

Keywords:

Two-Factor Authentication, User-Centric Security, Image-Based Authentication, Graphical Passwords, Cybersecurity, Access Control, Personalized Authentication

Abstract

In the wake of the rising digital world, traditional username/password-based authentications are facing an increased risk of being compromised by various cyber attacks, including phishing, brute force attacks, credential stuffing, and artificial intelligence-based impersonation attacks. While traditional two-factor authentications provide better security than traditional username/password-based authentications, these methods often bring their own set of problems, including usability issues. To overcome the limitations of traditional two-factor authentication, this paper proposes a two-factor authentication system based on traditional username/password-based authentication and image/keyword-based authentication. The system utilizes the capabilities of human visual memory to provide better security with minimal cognitive overhead for the users. The system utilizes secure cryptographic techniques to ensure the security of the system, keyword-based image verification to prevent replay attacks, and device-based restriction techniques to prevent brute force attacks. The system is developed based on the client-server model using the Django framework. The experimental results confirm that the proposed authentication system achieves an optimal balance between usability and security, making it a feasible solution for web application security.

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