User Authentication Through Mouse Dynamics
Use as Biometric Data[edit source | editbeta]
Researchers are interested in using this keystroke dynamic information, which is normally discarded, to verify or even try to determine the identity of the person who is producing those keystrokes. This is often possible because some characteristics of keystroke production are as individual as handwriting or a signature. The techniques used to do this vary widely in power and sophistication, and range from statistical techniques to neural-nets to artificial intelligence.
In the simplest case, very simple rules can be used to rule out a possible user. For example, if we know that John types at 20 words per minute, and the person at the keyboard is going at 70 words per minute, it's a pretty safe bet that it's not John. That would be a test based simply on raw speed uncorrected for errors. It's only a one-way test, as it's always possible for people to go slower than normal, but it's unusual or impossible for them to go twice their normal speed.
Or, it may be that the mystery user at the keyboard and John both type at 50 words per minute; but John never really learned the numbers, and always has to slow down an extra half-second whenever a number has to be entered. If the mystery user doesn't slow down for numbers, then, again, it's a safe bet this isn't John.
The time to get to and depress a key (seek-time), and the time the key is held-down (hold-time) may be very characteristic for a person, regardless of how fast they are going overall. Most people have specific letters that take them longer to find or get to than their average seek-time over all letters, but which letters those are may vary dramatically but consistently for different people. Right-handed people may be statistically faster in getting to keys they hit with their right hand fingers than they are with their left hand fingers. Index fingers may be characteristically faster than other fingers to a degree that is consistent for a person day-to-day
Researchers are interested in using this keystroke dynamic information, which is normally discarded, to verify or even try to determine the identity of the person who is producing those keystrokes. This is often possible because some characteristics of keystroke production are as individual as handwriting or a signature. The techniques used to do this vary widely in power and sophistication, and range from statistical techniques to neural-nets to artificial intelligence.
In the simplest case, very simple rules can be used to rule out a possible user. For example, if we know that John types at 20 words per minute, and the person at the keyboard is going at 70 words per minute, it's a pretty safe bet that it's not John. That would be a test based simply on raw speed uncorrected for errors. It's only a one-way test, as it's always possible for people to go slower than normal, but it's unusual or impossible for them to go twice their normal speed.
Or, it may be that the mystery user at the keyboard and John both type at 50 words per minute; but John never really learned the numbers, and always has to slow down an extra half-second whenever a number has to be entered. If the mystery user doesn't slow down for numbers, then, again, it's a safe bet this isn't John.
The time to get to and depress a key (seek-time), and the time the key is held-down (hold-time) may be very characteristic for a person, regardless of how fast they are going overall. Most people have specific letters that take them longer to find or get to than their average seek-time over all letters, but which letters those are may vary dramatically but consistently for different people. Right-handed people may be statistically faster in getting to keys they hit with their right hand fingers than they are with their left hand fingers. Index fingers may be characteristically faster than other fingers to a degree that is consistent for a person day-to-day