Fortifying Digital Security: A Machine Learning and Explainable AI Framework for Password Strength Assessment

In the current era where almost anything is accessible over the internet, passwords have become most important to ensure security and authentication. To provide authentication many other mechanisms exist like smart locks, biometrics, voice recognition, face recognition, etc. but still, passwords exist as the widely preferred method for authentication because of its ease of use and as many people are familiar with passwords. With the ease of use that it comes with there is a possible threat of guessing the passwords that exists. Usually, the passwords are some patterns, names, important years, etc. These are sometimes repetitive or easily guessed by the attacker because of their simplicity, and having common and weak passwords. The proposed model is a machine-learning algorithms that classifies the passwords as weak, medium, and strong based on their strength. Machine learning models like Random Forest (RF) classifier, Logistic Regression, XGBoost (XGB), and Gradient Boosting Machines (GBM).