Whenever you interface with the physical world around you, you inevitably leave traces - fingerprints, DNA material, behavioural patterns - that are uniquely identifiable. To an extent, you can choose what to touch or how to touch it, but ultimately every action leaves a trail inextricably linked to your identity.
The same is true for the digital world. We often discuss the collection of our personal data online, referring to both content and metadata. However already during the creation of such data, while interfacing with our devices, we leave a trace. This 'behavioural data' can be captured, collected, and used to track or imitate us, forming a digital fingerprint.
Deceit Board v1 (version 1) is a device that alters your keyboard biometric. It uses a Teensy board to intercept keyboard signals and is capable of altering your own keyboard biometric or assuming the identity (spoofing) of another keyboard user.
deceit board v1
Deceit Board v2 is currently in development and features a memory card slot.
Write mode: keystrokes are processed and used to refine your own typing-profile-model which is stored on the memory card; in this mode, keystrokes are anonymised through random delays.
Read mode: keystrokes are altered based on whichever memory card is inserted; this lets you assume different typing identities and exchange keystroke patterns with your friends.
deceit board v2 (in development)
Much more of this:
This project is part of a wider exploration of typing patterns. Please also checkout:
Keystroke Rhythm Reverse (in development), matches typing patterns to key values using machine learning and a dataset of 4 million tracked keystrokes.
The trained model will eventually allow to reconstruct the content of a typed text solely on the basis of sound/the audible typing rhythm.
Keyprints, a side project that is meant to better explain the concept of behavioural keystroke biometrics for people unfamiliar to the subject.