CyberSecDome: Difference between revisions
Created page with "=== CyberSecDome Project === {| class='wikitable' style='margin:auto' |- ! CORDIS Reference !! Start date !! End date !! Coordinator |- | https://cordis.europa.eu/project/id/101120779 || 01/09/2023 || 31/08/2026 || MAGGIOLI SPA / Italy |} === Project description === Organisations across the sectors significantly benefit from digital transformation to support evolving business models, services and customer experience. Despite the benefits of digital infrastructure adop..." |
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=== Project description === | === Project description === | ||
Organisations across the sectors significantly benefit from digital transformation to support evolving business models, services and customer experience. Despite the benefits of digital infrastructure adoption, there are numerous security challenges that could pose any digital disruption and risks for the critical service delivery and overall business continuity. There is a need to understand the overall digital infrastructure context and analyse and predict the possible threats and incidents in real-time so that quick and accurate responses can be taken into consideration for ensuring resilience of service delivery. Additionally, collaborative response and sharing of threat intelligence information is necessary to create overall awareness and increase the response capability of all stakeholders within the ecosystem. CyberSecDome will integrate advanced virtuality reality (VR) to extend the capability of the security solutions aiming to enhance security, privacy and resilience of the Digital Infrastructure. The project will consider AI-enabled security solutions to provide a better prediction of cybersecurity threats and related risks towards an efficient and dynamic incident management and optimise collaborative response among the stakeholders within the Digital Infrastructure ecosystem. CyberSecDome project is built on a collaboration of 15 organisations from 6 EU member states (IT, DE, IE, SE, EL, CY) and 2 affiliated countries (UK, CH), which is composed by 5 industrial partners, 6 scientific partners and 5 SMEs. The project will be coordinate by MAGGIOLI SPA. | Organisations across the sectors significantly benefit from digital transformation to support evolving business models, services and customer experience. Despite the benefits of digital infrastructure adoption, there are numerous security challenges that could pose any digital disruption and risks for the critical service delivery and overall business continuity. There is a need to understand the overall digital infrastructure context and analyse and predict the possible threats and incidents in real-time so that quick and accurate responses can be taken into consideration for ensuring resilience of service delivery. Additionally, collaborative response and sharing of threat intelligence information is necessary to create overall awareness and increase the response capability of all stakeholders within the ecosystem. CyberSecDome will integrate advanced virtuality reality (VR) to extend the capability of the security solutions aiming to enhance security, privacy and resilience of the Digital Infrastructure. The project will consider AI-enabled security solutions to provide a better prediction of cybersecurity threats and related risks towards an efficient and dynamic incident management and optimise collaborative response among the stakeholders within the Digital Infrastructure ecosystem. CyberSecDome project is built on a collaboration of 15 organisations from 6 EU member states (IT, DE, IE, SE, EL, CY) and 2 affiliated countries (UK, CH), which is composed by 5 industrial partners, 6 scientific partners and 5 SMEs. The project will be coordinate by MAGGIOLI SPA. | ||
=== Project outputs === | |||
==== Publications ==== | |||
{| class="wikitable sortable" | |||
! Domain !! Type of output !! Title !! DOI URL | |||
|- | |||
| AI, Machine Learning & Data Science || Peer reviewed articles || Sensors || https://doi.org/10.3390/s24154859 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || PTPsec: Securing the Precision Time Protocol Against Time Delay Attacks Using Cyclic Path Asymmetry Analysis || https://doi.org/10.5281/ZENODO.14806692 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Enhancing Malware Detection through Machine Learning using XAI with SHAP Framework || https://doi.org/10.5281/zenodo.14832484 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Security Challenges in Autonomous Systems Design || https://doi.org/10.1007/978-3-031-81981-0_13 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Synthetic Data Generation and Impact Analysis of Machine Learning Models for Enhanced Credit Card Fraud Detection || https://doi.org/10.5281/zenodo.14832599 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Securing Real-Time Systems using Schedule Reconfiguration || https://doi.org/10.5281/zenodo.14806788 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Similarity-Based Selective Federated Learning for Distributed Device-Specific Anomaly Detection || https://doi.org/10.1109/NOMS59830.2024.10575258 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Shells Bells: Cyber-Physical Anomaly Detection in Data Centers || https://doi.org/10.5281/zenodo.14807181 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Creating a Security Enforcement Environment for a Vehicular Platform || https://doi.org/10.5281/zenodo.10282179 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Conference proceedings || Advanced IDPS Architecture for Connected and Autonomous Vehicles || https://doi.org/10.5281/zenodo.14806852 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Other || REACT: Autonomous intrusion response system for intelligent vehicles || https://doi.org/10.48550/arxiv.2401.04792 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Peer reviewed articles || Cyber Threat Assessment and Management for Securing Healthcare Ecosystems using Natural Language Processing || https://doi.org/10.1007/S10207-023-00769-W | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Peer reviewed articles || Federated Learning-Based Personalized Recommendation Systems: An Overview on Security and Privacy Challenges || https://doi.org/10.1109/TCE.2023.3318754 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Peer reviewed articles || Digital Twins-enabled Zero Touch Network: A smart contract and explainable AI integrated cybersecurity framework || https://doi.org/10.1016/j.future.2024.02.015 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Peer reviewed articles || Generative AI and Cognitive Computing-Driven Intrusion Detection System in Industrial CPS || https://doi.org/10.5281/zenodo.13254989 | |||
|- | |||
| Cybersecurity, Privacy & Blockchain || Peer reviewed articles || Vulnerability detection using BERT based LLM model with transparency obligation practice towards trustworthy AI || https://doi.org/10.1016/j.mlwa.2024.100598 | |||
|} | |||
==== Technological assets ==== | |||
{| class="wikitable sortable" | |||
! Title !! Type of Asset !! Link / DOI !! Description | |||
|- | |||
| REACT: Autonomous intrusion response system || Software / Framework || https://doi.org/10.48550/arxiv.2401.04792 || Autonomous intrusion response system tailored for intelligent vehicles. | |||
|- | |||
| Shells Bells || Software / Framework || https://doi.org/10.5281/zenodo.14807181 || A cyber-physical anomaly detection framework designed for data centers. | |||
|- | |||
| PTPsec || Software Code || https://doi.org/10.5281/ZENODO.14806692 || A security tool designed to protect the Precision Time Protocol against time delay attacks using cyclic path asymmetry analysis. | |||
|} | |||
Latest revision as of 13:43, 22 April 2026
CyberSecDome Project
| CORDIS Reference | Start date | End date | Coordinator |
|---|---|---|---|
| https://cordis.europa.eu/project/id/101120779 | 01/09/2023 | 31/08/2026 | MAGGIOLI SPA / Italy |
Project description
Organisations across the sectors significantly benefit from digital transformation to support evolving business models, services and customer experience. Despite the benefits of digital infrastructure adoption, there are numerous security challenges that could pose any digital disruption and risks for the critical service delivery and overall business continuity. There is a need to understand the overall digital infrastructure context and analyse and predict the possible threats and incidents in real-time so that quick and accurate responses can be taken into consideration for ensuring resilience of service delivery. Additionally, collaborative response and sharing of threat intelligence information is necessary to create overall awareness and increase the response capability of all stakeholders within the ecosystem. CyberSecDome will integrate advanced virtuality reality (VR) to extend the capability of the security solutions aiming to enhance security, privacy and resilience of the Digital Infrastructure. The project will consider AI-enabled security solutions to provide a better prediction of cybersecurity threats and related risks towards an efficient and dynamic incident management and optimise collaborative response among the stakeholders within the Digital Infrastructure ecosystem. CyberSecDome project is built on a collaboration of 15 organisations from 6 EU member states (IT, DE, IE, SE, EL, CY) and 2 affiliated countries (UK, CH), which is composed by 5 industrial partners, 6 scientific partners and 5 SMEs. The project will be coordinate by MAGGIOLI SPA.
Project outputs
Publications
| Domain | Type of output | Title | DOI URL |
|---|---|---|---|
| AI, Machine Learning & Data Science | Peer reviewed articles | Sensors | https://doi.org/10.3390/s24154859 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | PTPsec: Securing the Precision Time Protocol Against Time Delay Attacks Using Cyclic Path Asymmetry Analysis | https://doi.org/10.5281/ZENODO.14806692 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | Enhancing Malware Detection through Machine Learning using XAI with SHAP Framework | https://doi.org/10.5281/zenodo.14832484 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | Security Challenges in Autonomous Systems Design | https://doi.org/10.1007/978-3-031-81981-0_13 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | Synthetic Data Generation and Impact Analysis of Machine Learning Models for Enhanced Credit Card Fraud Detection | https://doi.org/10.5281/zenodo.14832599 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | Securing Real-Time Systems using Schedule Reconfiguration | https://doi.org/10.5281/zenodo.14806788 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | Similarity-Based Selective Federated Learning for Distributed Device-Specific Anomaly Detection | https://doi.org/10.1109/NOMS59830.2024.10575258 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | Shells Bells: Cyber-Physical Anomaly Detection in Data Centers | https://doi.org/10.5281/zenodo.14807181 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | Creating a Security Enforcement Environment for a Vehicular Platform | https://doi.org/10.5281/zenodo.10282179 |
| Cybersecurity, Privacy & Blockchain | Conference proceedings | Advanced IDPS Architecture for Connected and Autonomous Vehicles | https://doi.org/10.5281/zenodo.14806852 |
| Cybersecurity, Privacy & Blockchain | Other | REACT: Autonomous intrusion response system for intelligent vehicles | https://doi.org/10.48550/arxiv.2401.04792 |
| Cybersecurity, Privacy & Blockchain | Peer reviewed articles | Cyber Threat Assessment and Management for Securing Healthcare Ecosystems using Natural Language Processing | https://doi.org/10.1007/S10207-023-00769-W |
| Cybersecurity, Privacy & Blockchain | Peer reviewed articles | Federated Learning-Based Personalized Recommendation Systems: An Overview on Security and Privacy Challenges | https://doi.org/10.1109/TCE.2023.3318754 |
| Cybersecurity, Privacy & Blockchain | Peer reviewed articles | Digital Twins-enabled Zero Touch Network: A smart contract and explainable AI integrated cybersecurity framework | https://doi.org/10.1016/j.future.2024.02.015 |
| Cybersecurity, Privacy & Blockchain | Peer reviewed articles | Generative AI and Cognitive Computing-Driven Intrusion Detection System in Industrial CPS | https://doi.org/10.5281/zenodo.13254989 |
| Cybersecurity, Privacy & Blockchain | Peer reviewed articles | Vulnerability detection using BERT based LLM model with transparency obligation practice towards trustworthy AI | https://doi.org/10.1016/j.mlwa.2024.100598 |
Technological assets
| Title | Type of Asset | Link / DOI | Description |
|---|---|---|---|
| REACT: Autonomous intrusion response system | Software / Framework | https://doi.org/10.48550/arxiv.2401.04792 | Autonomous intrusion response system tailored for intelligent vehicles. |
| Shells Bells | Software / Framework | https://doi.org/10.5281/zenodo.14807181 | A cyber-physical anomaly detection framework designed for data centers. |
| PTPsec | Software Code | https://doi.org/10.5281/ZENODO.14806692 | A security tool designed to protect the Precision Time Protocol against time delay attacks using cyclic path asymmetry analysis. |