Keystroke biometric algorithms have advanced to the point where it is viable to fingerprint users based on soft biometric traits. This is a privacy risk because masking spatial information -- such as the IP address via Tor -- is insufficient to anonymize users. 
Users can be uniquely fingerprinted based on: 
- Typing speed.
- Exactly when each key is located and pressed (seek time), how long it is held down before release (hold time), and when the next key is pressed (flight time).
- How long the breaks/pauses are in typing.
- How many errors are made and the most common errors produced.
- How errors are corrected during the drafting of material.
- The type of local keyboard that is being used.
- Whether they are likely right or left-handed.
- Rapidity of letter sequencing indicating the user's likely native language.
A unique neural algorithm generates a primary pattern for future comparison. It is thought that most individuals produce keystrokes that are as unique as handwriting or signatures. This technique is imperfect; typing styles can vary during the day and between different days depending on the user's emotional state and energy level. 
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