Code for the paper Analysis and Detectability of Offline Data Poisoning Attacks on Linear Systems.
Author: Alessio Russo (alessior@kth.se)
License: MIT
To run the examples you need the following libraries: numpy scipy cvxpy dccp momentchi2 torch matplotlib. See also the requirements file requirements.txt.
To run the example, run the file main.py in the folder example_input_attack. Feel free to change the standard deviation of the process noise std_w, or of the input signal std_u.
To run the example, run the file main.py in the folder example_residuals_maximization. Use plot_data.py to plot the results.
To use the data of the paper, first extract the data from the zipped files example_residuals_maximization\data\compressed_data.*.zip in the data folder.
All the data used in the papers can be found in the folder example_stealthy_attack\data.
To plot the data use the analyse_results.py file.
To run a new set of simulations use extract_data.py to collect the datasets, and algorithm.py to compute the poisoning attack using SLSQP.
