Multiclass Password Strength Classification (MPSC 2024) Dataset for password cracking detection and prevention

We present a novel cutting-edge, large-scale multiclass dataset to improve the security of password protected systems cognition of suspicious password cracking attempts. The proposed newly generated dataset contains up-to-date samples and features available to the public to help reduce the effect of upcoming cyberattacks with machine learning methods. Specifically, 700,000 samples with more than 100 features are collected, processed through several stages including hashing, tokenization (NLP techniques), an others, and organized into three password classes: weak, moderate, and strong. For detailed info, Please refer to and cite our articles: Al-Haija, Q.A., Abu-Ghazaleh, R., Hafez, A., Mansour, S., Aljammal, Y. (2024). Password Security: Cracking Techniques and Countermeasures. Proceedings of Data Analytics and Management. ICDAM 2024. Lecture Notes in Networks and Systems, Springer, 2024. Al-Haija, Q.A., Abu-Ghazaleh, R., Hafez, A., Mansour, S., Aljammal, Y. (2024). PasswordProtectorPro: A Password Cracking Detection and Prevention Tool for Mission Critical Systems. 8th IET Smart Cities Symposium (SCS 2024), Hybrid Conference, Bahrain, 2024.