ACOLYTE (dAta Curation fOr traceabiLity sYsTEm)

ACOLYTE is a Python application designed to facilitate traceability in autonomous systems in a cibersecure manner. It has been developed to assist in the automated extraction of data from autonomous systems. The application is available in the form of a command-line tool. Two fundamental options are available:

• Store records.
  • Reading information from a ROS bag file.
  • Reading information from the vehicle's OBD-II port.
• Get stored records by a timeframe.

This Python application is dependant on BCubed Python library. BCubed is available at BCubed repository.

⚠️ Disclaimer

This Python application has only been tested in simulated blockchain environments. Using it in other environments is at your own risk. Keep possible charges in mind.

Getting Started

Create and activate a virtual enviroment (recommended)

$ python3 -m venv .venv
$ source .venv/bin/activate

Install the requirements

(.venv) pip install -r requirements.txt

Install BCubed Python library

Follow the instructions available in BCubed README.md. It is important to note that the virtual environment has already been created.

Install ACOLYTE

(.venv) $ pip install -e <acolyte_location>

Execute ACOLYTE

1. Ensure the blockchain network is available.

   • (Optional) Execute an Ethereum simulator.

2. Update the configuration data in the bcubed-config.yaml file.

3. Configure the environment variable named BCUBED_CONF_FILE to set the bcubed-config.yaml path. By default, it is set to ./bcubed-config.yaml.

Store records

1. Reading information from a ROS bag file

4. Update the configuration data in the topics-config.yaml file.

5. Configure the environment variable named ACOLYTE_CONF_FILE to set the topics-config.yaml path. By default, it is set to ./topics-config.yaml.

6. Execute the following command:

   (.venv) $ acolyte -a store -i <rosbag2_file> -r <responsible> -w rosbag
   

7. To monitor operating system information too, execute the following command:

   (.venv) $ acolyte -a store -i <rosbag2_file> -r <responsible> -w rosbag -os
   

2. Reading information from the vehicle's OBD-II port

4. Update the configuration data in the obd-config.yaml file.

5. Configure the environment variable named ACOLYTE_CONF_FILE to set the obd-config.yaml path. By default, it is set to ./topics-config.yaml.

6. Execute the following command:

   (.venv) $ acolyte -a store -i /dev/null <responsible> -w obd
   

3. Reading information from an Excel file with OBD-II data

4. Update the configuration data in the obd-config.yaml file:

   • In the excel_obd section, map the Excel column names to the internal OBD field names.
   • Use the exact column names from your Excel file as values.
   • Leave empty ('') for fields not present in your Excel.

5. Configure the environment variable named ACOLYTE_CONF_FILE to set the obd-config.yaml path. By default, it is set to ./topics-config.yaml.

6. Execute the following command:

   (.venv) $ acolyte -a store -i <excel_file> -r <responsible> -w obd_excel
   

Get stored records by a timeframe

1. Execute the following command:

(.venv) $ acolyte -a get_by_timestamp -ts <timestamp_start> -te <timestamp_end>

Uninstall ACOLYTE

(.venv) $ pip uninstall acolyte

Dataset available

A dataset has been created to facilitate testing of the application without the need to create your own rosbag. It is available at the following URL: https://zenodo.org/records/16630061.

Acknowledgements

This research is part of the project TESCAC, financed by “European Union NextGeneration-EU, the Recovery Plan, Transformation and Resilience, through INCIBE".