The project focuses on researching and developing an open-source platform for extracting, processing, and analyzing cyberattacks traffic and its impacts on companies and society. For that, SecGrid implements a set of extensible miners and visualizations that allows non-experts users to have insights about behaviors of cyberattacks. Also, the project supports a set of tools and features built on the top of the SecGrid architecture for machine learning analysis and classification of cyberattacks, information sharing, and cybersecurity planning.
|Source of funding:||UZH and CONCORDIA H2020|
|Project Duration:||from 2019 to 2022|
A running prototype of the platform is available here. Please use the follow credentials to log-in:
* For a better experience and demonstration for the users, the upload of new files are disabled with this credential. Feel free to test the different features using the sample datasets provided. If you want to have credentials for full access (i.e., upload new files) to the platform, please send a message to email@example.com
ML Training Dataset: Link
* A file with all PCAP files used for the training and evaluation of the ML classification is available here.