Deliverables
Integrated AI-based attack detection methods to detect advanced threats, along with documentation
An initial prototype of the AI-based algorithms for threat identification and trend prediction with an API, including documentation
Initial prototype versions of Infrastructure Modelling component and basic version of Attack Defence Graph analyser, along with documentation. The components will be limited towards application scenarios relevant for the first pilot iteration.
This deliverable presents the initial version of the orchestration and integration component, reconfiguration component and web front-end component. We describe the communications they provide, functionalities they cover, plan for evaluation and integration in the SOCCRATES Platform.
Contains the progress of dissemination activities and standardization activities
Specification of the model for quantification of business impact, including the concepts and structures of the model language.
This deliverable describes the initial version of the system architecture and interface specification. It will include a detailed description of the components and the interfaces
Contains all plans of SOCCRATES for dissemination at events and to stakeholders
A compact (online) handbook for participants in the project, that contains all SOCCRATES practical project information
A plan in which the way data is handled in the project is described, including responsibilities and measures to protect data
This deliverable will describe the use cases that are representative for the usage of the SOCCRATES platform. In addition, the pilot sites will be described and requirements for the deployment of the SOCCRATES platform at these pilot sites
Online communication platform to communicate with and inform the SOCCRATES stakeholder group on progress of the project and relevant events
The project website (easy accessible) that contains actual information regarding the project and its events and where deliverables can be downloaded
Publications
Author(s): Andreas Gylling; Mathias Ekstedt; Zeeshan Afzal; Per Eliasson
Published in: 2021 IEEE International Conference on Cyber Security and Resilience (CSR), 2021
Publisher: IEEE
DOI: 10.1109/csr51186.2021.9527970
Author(s): Martin Teuffenbach, Ewa Piatkowska, Paul Smith
Published in: nternational IFIP Cross Domain (CD) Conference for Machine Learning & Knowledge Extraction (MAKE) 2020, August 25 2020, 2020, Page(s) 301-320
Publisher: Springer
DOI: 10.1007/978-3-030-57321-8_17
Author(s): Irina Chiscop
Francesca Soro
Paul Smith
Published in: NativeNi '22: Proceedings of the 1st International Workshop on Native Network Intelligence, December 2022, 2022, Page(s) Pages 27–32
Publisher: ACM digital library
DOI: 10.1145/3565009.3569523
Author(s): WOJCIECH WIDEŁ, PREETAM MUKHERJEE, AND MATHIAS EKSTEDT
Published in: IEEE Access, Volume 10, 2021, Page(s) 89645 - 89662, ISSN 2169-3536
Publisher: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2022.3200601
Author(s): Sotirios Katsikeas, Simon Hacks, Pontus Johnson, Mathias Ekstedt, Robert Lagerström, Joar Jacobsson, Max Wällstedt, Per Eliasson
Published in: Graphical Models for Security - 7th International Workshop, GraMSec 2020, Boston, MA, USA, June 22, 2020, Revised Selected Papers, 12419, 2020, Page(s) 67-86, ISBN 978-3-030-62229-9
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-62230-5_4