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Multi-Partner Project: CyberSecDome - Framework for Secure, Collaborative, and Privacy-Aware Incident Handling for Digital Infrastructure

  • Mohammad Hamad
  • , Michael Kühr
  • , Haralambos Mouratidis
  • , Eleni Maria Kalogeraki
  • , Christos Gizelis
  • , Dimitris Papanikas
  • , Athanasios Bountioukos-Spinaris
  • , Charilaos Skandylas
  • , Evangelos Raptis
  • , Andreas Alexopoulos
  • , Grigorios Chrysos
  • , Mina Marmpena
  • , Sevasti Politi
  • , Konstantinos Lieros
  • , Papagiannopoulos Nikolaos
  • , Iordanis Xanthopoulos
  • , Spyros Papastergiou
  • , Sotiris Ioannidis
  • , Mikael Asplund
  • , Marc Oliver Pahl
  • Sebastian Steinhorst
  • Technical University of Munich
  • Security Labs Consulting
  • University of Essex
  • Hellenic Telecommunications Organisation
  • CyberAlytics Ltd.
  • Linköping University
  • Aegis It Research
  • Technical University of Crete
  • Internet of Things applications and Multi-Layer development
  • Athens International Airport S.A.
  • Sphynx
  • Maggioli S.p.A.
  • Technopôle Brest-Iroise

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Digital infrastructure is vital for the economy, democracy, and everyday life, yet it is becoming increasingly vulnerable to strategic cyber-attacks. These attacks can lead to significant disruptions, resulting in widespread service outages, financial losses, and a decline in public trust. Ensuring resilience is difficult due to the infrastructure's complexity, the large volume of data involved, and the growing need for quick, coordinated responses. In the EU Horizon project CyberSecDome, we propose a multi-layered framework that provides AI-driven solutions for incident prediction and detection, automated testing, risk assessment, and rapid incident response, supporting continuity amid complex, large-scale cyber threats. Additionally, Cyber-SecDome introduces a virtual reality interface to enhance AI model explainability and provide real-time contextual awareness of ongoing attacks and defense mechanisms. It also enables privacy-aware model sharing across AI systems, fostering secure collaboration among different domes.

Original languageEnglish
Title of host publication2025 Design, Automation and Test in Europe Conference, DATE 2025 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9783982674100
DOIs
StatePublished - 2025
Event2025 Design, Automation and Test in Europe Conference, DATE 2025 - Lyon, France
Duration: 31 Mar 20252 Apr 2025

Publication series

NameProceedings -Design, Automation and Test in Europe, DATE
ISSN (Print)1530-1591

Conference

Conference2025 Design, Automation and Test in Europe Conference, DATE 2025
Country/TerritoryFrance
CityLyon
Period31/03/252/04/25

Keywords

  • AI
  • Incident handling
  • Intrusion detection
  • Security

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