Click here to download the dataset for our paper “Exploring Intentional Behaviour Modifications for Password Typing on Mobile Touchscreen Devices”.
Content
- A data folder, containing pre-processed data from both study sessions
- A Jupyter notebook containing a model using random forest classification to distinguish normal and modified keypresses.
- A results folder for saving the detection results.
Usage
With Jupyter and Python 3.x(with packages numpy, pandas, sklearn and pickle) installed, execute ‘jupyter notebook’ inside the folder and run all cells subsequently. Note, that your results may differ slightly due to the use of random seeds.
Publication
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Lukas Mecke, Daniel Buschek, Mathias Kiermeier, Sarah Prange and Florian Alt. Exploring Intentional Behaviour Modifications for Password Typing on Mobile Touchscreen Devices. In Fifteenth Symposium on Usable Privacy and Security (SOUPS 2019). USENIX Association, Santa Clara, CA. [Download Bibtex] |