This code package is related to the paper:
M. Nerini, E. Favarelli, and M. Chiani, "Machine Learning for PIN Side-Channel Attacks Based on Smartphone Motion Sensors," IEEE Access, 2023.
The dataset.txt
file contains a 5400 x 17 matrix in which:
- each row is a sampled digit.
- each column is a feature: the first is the pressed digit and the following are motion sensor values.
The PIN_recognition.ipynb
Jupiter Notebook contains the code to replicate the results in the paper.
The files rf-prod.csv
, svm-prod.csv
, mlp-prod.csv
, and knn-sum.csv
have been obtained throguh PIN_recognition.ipynb
and are attached for an easier replication of the figures.