Password Strength Meter and Generator (ASPIRE)
Our project consists of a website that allows a user to measure the strength of their password using a Password Strength Meter (PSM) and also generate a password using a Password Generator. The goal of the generator was to provide the option of creating a strong password for the user based on some user inputs so that it could be remembered somewhat easily.
The PSM takes in a password as an input and gives a score from 0-4 with 0 being the weakest and easily guessable to 4 being strong and not easily guessable. It uses the zxcvbn password strength meter as a base and additionally incorporates a spellchecker which has the ability to assess passwords that consist of misspelled words. This is a new addition as the original zxcvbn algorithm couldn’t accurately measure the strength of passwords based on misspelled words and thus would give higher scores to passwords based on misspelled words even when they weren’t.
In the situation that the user is having trouble creating a strong password, we also incorporated a password generator into the website. The generator takes in 5 user inputs, 3 text inputs that are between 4-9 characters and 2 numbers. It does various random functions on the input and creates a password that somewhat resembles the original words entered so the user can easily remember it, but is not easily guessable.
The project is not finished as you will notice that the passwords created by the generator are not quite as readable as we hoped. More research needs to be done regarding the characteristics of passwords and perhaps even a better algorithm to create them. In addition we noticed that some passwords which did not seem ‘strong’ from a user perspective got a score of 4/4. Thus zxcvbn may not be as strong as people think and may need to be further modified.
Link to website/project: https://aspire547.glitch.me/
Link to report: https://docs.google.com/document/d/1TtwTll2f1gdJnGa-WFRNaA1Dz9eDdPzMpm2wv6OU3h4/edit?usp=sharing
Anjali Toly, CE, 2022, atoly@umass.edu
Kevin Zheng, CE, 2022, kyzheng@umass.edu
Mahima Jaikanth, CE, 2022, mjaikanth@umass.edu
Nandini Sivakumar, CE, 2022, nsivakumar@umass.edu
Sanjana Kaza, CE, 2022, skaza@umass.edu
