The meter works by employing an artificial neural network: a large, complex map of information that resembles the way neurons behave in the brain.
The network "learns" by scanning millions of existing passwords and identifying trends.
If the meter detects a characteristic in your password that it knows attackers may guess, it will tell you.
"Our new meter led users to create stronger passwords that were no harder to remember than passwords created without the feedback," said said Blase Ur, assistant professor at the University of Chicago in the US.
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"Instead of just having a meter say, 'Your password is bad,' we thought it would be useful for the meter to say, 'Here's why it's bad and here's how you could do better,'" said Nicolas Christin, a professor at Carnegie Mellon University in the US.
The key result is that providing the data-driven feedback actually makes a huge difference in security compared to just having a password labelled as weak or strong.
"The way attackers guess passwords is by exploiting the patterns that they observe in large datasets of breached passwords," said Ur.
This data-driven feedback is presented in real-time, as a user is typing their password out letter-by-letter.
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