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CyberSignature was born out of curiousity to use behavioural biometrics to create unique digital identities that can be used during online card transactions to distinguish legitimate users from fraudsters. The tool is implemented in Python, with a machine learning algorithm at its core. It receives user input data entries from a graphical user interface, similar to an online payment form, and transforms them into unique digital identities. The home screen is shown below:

This section lists any major frameworks/libraries used to bootstrap the project.

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This documentation assumes that the user has Python 3 installed on their machine and also know how to setup a python environment for a project locally. To get a local copy of CyberSignature up and running follow these simple example steps.

You must install the following Python packages to run the software.

Package         Version
------------    ------------
python          3.8.8
numpy           1.21.5
pandas          1.4.4
kivy            2.0.0
scikit-learn    1.1.1

Below is an example of how you can download the CyberSignature project from Github and execute the application locally.

1. Clone the repo

   git clone https://github.com/CyberSignature-EHU/CyberSignature.git

2. create a Python environment for the CyberSignature project called project/, which has the following directory tree.

   project/
   |
   |_ false_data/
   |_ saved_models/
   |_ application.py
   |_ cs_logo.png
   |_ ehu_logo.png
   

3. Install prerequisite packages above
4. Run the application.py file to open the application

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For an example of how to use the application, please view the demonstrator video here.

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N. Nnamoko, J. Barrowclough, M. Liptrott, and I. Korkontzelos, “CyberSignature: a user authentication tool based on behavioural biometrics,” Elsevier Softw. Impacts, 2022.

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Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. Don't forget to give the project a star! Thank you!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/NewFeature)
3. Commit your Changes (git commit -m 'Add some NewFeature')
4. Push to the Branch (git push origin feature/NewFeature)
5. Open a Pull Request

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Distributed under the .

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Name: Nonso Nnamoko
e-mail: [email protected]

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The CyberSignature Project received two rounds of funding from Innovate UK under CyberASAP with Project Reference No. 10017354 and 10002115. Special thanks to KTN who facilitated the project delivery and to the Computer Science Department at Edge Hill University, for providing time and resources to complete the project. The authors would also like to acknowledge participants who contributed KMT dynamics dataset for the software development and validation.

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