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.
- Keyboard Layout as the placement of the keys on the keyboard leads to different key seek times and typing mistakes.
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. 
Unless protective steps are taken to obfuscate the time intervals between key press and release events, it is likely most users can be deanonymized based on their keystroke manner and rhythm biometrics. Adversaries are likely to have samples of clearnet keystroke fingerprinting which they can compare with "anonymous" Tor samples.
Kloak is a Keystroke Anonymization Tool.
Kloak is installed in Non-Qubes-Whonix ™ Whonix-Workstation ™ 15 by default.
We recommend installing kloak on the host too so it remains effective in event of a Whonix-Workstation ™ VM compromise. If you need to access accounts (for example banking) that enforce keystroke biometrics, then it may be a good idea to just limit installation to Whonix ™ VMs.
You can test that kloak actually works by trying an online keystroke biometrics demo. For example, try these three different scenarios:
- Train normal, test normal
- Train normal, test kloak
- Train kloak, test kloak
Train normal means to train with normal typing behavior (without kloak running). At the enrollment page on the KeyTrac demo, enter a username and password without kloak running, and then on the authenticate page, try authenticating.
Expected results and interpretation:
Train normal, test normal
trial 1: 94% accuracy identified
trial 2: 92% accuracy
trial 3: 94% ..
Train normal, test kloak
trial 1: 18%
trial 2: 15%
trial 3: 19%
Train kloak, test kloak
trial 1: 40%
trial 2: 42%
trial 3 36%
Without kloak users can be identified with very high certainty. The second set of tests show that kloak definitely obfuscates typing behavior, making it difficult to authenticate or identify a particular user. Third set: users running kloak may look "similar" to other users running kloak. That is, it might be possible to identify kloak users from non-kloak users. If this is the case, the anonymity set will increase as more users start running kloak.
Planned future developments of kloak will focus on obfuscating unique mouse movement behavior to protect user anonymity.
- Mouse Fingerprinting
/dev/input/event0in Qubes VMs will not work since not a keyboard device.
- Feasibility of a Keystroke Timing Attack on Search Engines with Autocomplete