Password Data Analysis Module
In this module, we collected over 115 million real world passwords from well-known websites such as LinkedIn, Yahoo!, CSDN, and Renren. We provide means of categorizing passwords based on their properties and features, and users can use this module to conduct statistical study and preprocessing of new data.
Password Cracking Module
In this module we surveyed and implemented state-of-the-art password cracking algorithms including 7 from the academic research that were proposed after 2005. Users can use the algorithms easily in our system and compare the cracking performances or research for other purposes. This module is scalable as new algorithms can be easily added.
Password Measurement Module
In this module, we surveyed and implemented 15 strength metrics and 8 strength meters from academia, and 15 commercial password meters. The module is scalable to add new metrics/meters easily. Users can use this module to measure the strength of passwords and can combine it with the Password Cracking Module to perform in-depth research.
Password Data Analysis.
In this module, leveraging a large corpus (∼ 115M) of real-world passwords, we develop several analytical functions to characterize password datasets by computing the distributions of passwords in terms of length, structure, and composition. The strength distribution of passwords in terms of specific metrics/meters can also be computed by interacting with the corresponding module in PARS. This module enables users/researchers to conduct statistical analysis of password datasets. Furthermore, to conduct uniform and comparable analysis, researchers can construct standard datasets from the original password datasets.
In this module, we implement state-of-the-art password cracking algorithms, including 7 academic password cracking algorithms proposed after 2005. Using this module, users can evaluate the crackability of password datasets under different scenarios, which enables them to comprehensively understand the vulnerability of a password dataset. Researchers can also use this module to uniformly and comparatively study the existing/newly developed password cracking algorithms.
In this module, we implement 15 strength metrics and 8 strength meters from academia. We also implement 15 of the 24 commercial password meters with online and offline versions, of the top-15 websites in each of 10 categories (Business, Computers, Health, Science, Shopping, Society, News, Sports, Kids&Teens, and Home) ranked by Alexa. Using this module, users can evaluate the strength of passwords in terms of any academic metric, meter, and/or commercial meter, which can help them understand the security of their passwords. Further, researchers can systematically study, evaluate and compare the existing/newly developed metrics/meters.