A context-based password change enforcement model

Password-based authentication systems remain vulnerable to various cyber threats, highlighting the need for innovative approaches to enhance security. In this paper, we propose a context-based password change enforcement (PCE) model aimed at fortifying password-based authentication systems by dynamically evaluating password reliability through contextual parameters. Leveraging password frequency, uniqueness, attempt, environment, and age, these parameters were used to assess password security and enforce timely changes, thereby enhancing overall system resilience. The implementation of the PCE model led to a significant reduction in password compromise, with only 2 out of 450 user passwords compromised, representing a notable decrease of 96% compared to the initial 50 compromised passwords. Comparative analysis revealed a 99.99% performance rate of the proposed PCE model, outperforming other authentication methods. The PCE model therefore offers a systematic and effective approach to strengthen text-based password authentication systems, mitigating common password attacks and enhancing overall security posture.