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Classifying user based on typing signature. [Discussion]

Just an idea I had today. Everyone has idiosyncratic ways that they type from “high” level to “low” level: language use (vocab, phrases and idioms), misspellings, typos, speed and particular letter combinations that they hit more quickly than other people. It seems like you could, ignoring the semantic stuff for now, key log a thousand people (ethically) and get patterns of people’s typing behavior and discriminate a user based on their typing signature. I tend to leave my finger on my right hand longer on the right shift key so I often end up with ERrors like that <- when typing.

This approach has been used already: https://link.springer.com/chapter/10.1007/978-981-10-8180-4_4

But perhaps it could be applied to things like detecting unknown users native language based on common strings like “the” or “-ing” which native English users may type extra fast through practice as opposed to a native Chinese speaker typing in English. Perhaps you could create an algorithm that is able to discriminate country of origin / language of the person trying to access a controlled system or have some cybersecurity application.

Thoughts?

submitted by /u/ebolafever
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.