xrosliang / kido Goto Github PK

About kido:

Can we figure out what someone is typing, just by listening to the keystrokes?

This project called kido (= keystroke decode) explores if this is possible. It is published in Towards Data Science.

Quick start guide:

For training and validation: kido/code/kido_train.ipynb
Training data at: kido/images/train/
Validation data at: kido/images/dev/
The training and validation images are stored as per TensorFlow convention.
For example, all training images corresponding to keystroke m are stored in a subfolder images/train/m, and all validation images corresponding to keystroke m are stored in a subfolder images/dev/m, and so on.

For testing: kido/code/kido_test.ipynb
Specify the test dir, in this case: kido/batch99_test/
In the test dir make four sub-dirs called audio, images, model, and splits
Store the recorded keystrokes audio m4a (unsplitted) at: kido/batch99_test/audio/
Make sure the file name is the word itself (type only alphabets and all lowercase).
For example, iloveu.m4a should be the file name for the keystrokes audio typing iloveu.
The python script will automatically convert m4a to wav, split, and generate spectrograms.
Store the trained model at: kido/batch99_test/model/ and specify the file name in the script.

Note: All the data (train, dev, and test) in this study were collected using my MacBook Pro (Retina, 13-inch, Early 2015) keyboard.

Detail descriptions:

Coming soon ...

Resources:

Published in Towards Data Science: Clear and Creepy Danger of Machine Learning: Hacking Passwords

The rockyou passwords link: rockyou.txt