Data-Driven Password Meter

CUPS Research Lab, 2017 Best Paper Award at Computer Human Interaction (CHI)

I developed a user flow that considers 20+ password scoring metrics to give digestible tips and offer tailored suggestions to improve a typed password. The feedback emphasizes teaching the user what makes a weak/strong password so they will make better passwords in the future.

We tested this improved meter with 4,509 online participants and published the results in a paper at CHI 2017.

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