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Continuous and Efficient Cooperative Trust Management for Resilient CCAM

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Distributed Processing and CCAM Trust Functions Offloading & Data Space Modelling

State-of-the-art analysis of the most prominent orchestration and offloading techniques, within the MEC-Enhanced vehicular context, so as to identify those approaches that are most suitable for further investigation when it comes to assessing the feasibility and executing a trust calculation offloading action. Furthermore, this deliverable will document the data model, of the CONNECT VCs, by enhancing the standardized W3C model to also capture the required features of the target CCAM ecosystem.

Dissemination, Communication, Clustering and Exploitation activities

Documentation on the dissemination, communication, clustering, standardization, and exploitation activities. Highlighting open-source contributions and workshop organization activities. First version will be submitted in M18. Second version will be submitted in M36 and will exclude exploitation measures which will be included within Deliverable 7.3.

Project Quality Plan

A set of project templates, project management, review and internal quality control processes, and Open Science practices. The second part of D1.2, the Risk Assessment Plan, shows how potential risks are assessed and mitigated.

Operational Landscape, Requirements and Reference Architecture - Initial Version

Documentation of CONNET requirements (T2.1), CCAM services positioning (T2.2), first version of the overall Reference Architecture (T2.4), and first version of the ethical analysis (T2.3) on the measures of evidence to be considered during the CONNECT trust assessment & the type of system properties (T2.5) that can be attested.

Plan for Dissemination and Exploitation incl. Communication

Documentation on T7.1 and on the planned dissemination, exploitation and communication activities.

Architectural Specification of CONNECT Trust Assessment Framework, Operation and

Documentation of CONNECT Trust Assessment architecture & methodology (T3.1-3).

Distributed Processing, Fast Offloading and MEC-enabled Orchestrator

Documentation on the policy modelling and decision making for managing the offloading policies. This deliverable also provides the 1st release of the MEC-enabled CONNECT Orchestrator as well as the VCs for the continuous authorization, authentication and secure communication between CCAM actors.

Conceptual architecture of Customizable TEE and Attestation Models Specifications

Report on the progress of T4.1-3 on blueprinting the architecture of the customisable TEE Guard and all envisioned functionalities alongside the methodology for enforcing runtime behavioural attestation.

CONNECT Trust & Risk Assessment and CAD Twinning Framework (Initial Version)

Early release of CONNECT Trust Assessment framework with its internal Risk Assessment engine and first release of the Digital Twin component for the real-time offloading of the trust calculations.

Virtualization- and Edge-based Security and Trust Extensions (First Release)

Early release of the CONNECT Guard and TC-enabled DTs leveraging root-of-trust capabilities of the TEE-enabled connector for enabling the provision of implemented attestation enablers (T4.3) & runtime monitors (T4.4), including details on the implementation of the Secret Sharing scheme (T4.2).

Pubblicazioni

Hash-Based Direct Anonymous Attestation

Autori: Liqun Chen; Changyu Dong; Nada El Kassem; Christopher J. P. Newton; Yalan Wang
Pubblicato in: Post-Quantum Cryptography (PQCrypto 2023), 2024, ISBN 978-3-031-40003-2
Editore: Springer
DOI: 10.1007/978-3-031-40003-2_21

WIP: A Trust Assessment Method for In-Vehicular Networks using Vehicle Risk Assessment

Autori: Artur Hermann, Natasa Trkulja, Anderson Ramon Ferraz de Lucena, Alexander Kiening, Ana Petrovska, Frank Kargl
Pubblicato in: VehicleSec 2024, 2024, ISBN 979-8-9894372-7-6
Editore: NDSS
DOI: 10.14722/vehiclesec.2024.23016

Edge-assisted ML-aided Uncertainty-aware Vehicle Collision Avoidance at Urban Intersections

Autori: Dinesh Cyril Selvaraj, Christian Vitale, Tania Panayiotou, Panayiotis Kolios, Carla Fabiana Chiasserini, Georgios Ellinas
Pubblicato in: IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, ISSN 2379-8904
Editore: IEEE
DOI: 10.48550/arXiv.2404.14523

In-vehicle Trust Assessment Framework

Autori: Nataša Trkulja, Artur Hermann, Ana Petrovska, Alexander Kiening, Anderson Ramon Ferraz de Lucena, Frank Kargl
Pubblicato in: 21th ESCAR Europe 2023, 2023
Editore: Ruhr-Universität Bochum
DOI: 10.13154/294-10384

Comparative Evaluation of PKI and DAA-based Architectures for V2X Communication Security

Autori: Angelogianni Anna; Krontiris Ioannis; Giannetsos Thanassis
Pubblicato in: 2023 IEEE Vehicular Networking Conference (VNC), 2023, ISSN 2157-9865
Editore: IEEE
DOI: 10.1109/VNC57357.2023.10136316

Securing Cooperative Intersection Management through Subjective Trust Networks

Autori: Frank Kargl, Nataša Trkulja, Artur Hermann, Florian Sommer, Anderson Ramon Ferraz de Lucena, Alexander Kiening, Sergej Japs
Pubblicato in: 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), 2023, ISSN 2577-2465
Editore: IEEE
DOI: 10.1109/VTC2023-Spring57618.2023.10200789

S-LDM: Server Local Dynamic Map for 5G-based Centralized Enhanced Collective Perception

Autori: Carlos Mateo Risma Carletti, Francesco Raviglione, Claudio Casetti, Filippo Stoffella, Girma Mamuye Yilma, Filippo Visintainer
Pubblicato in: Journal Vehicular Communication, 2023, ISSN 2577-2465
Editore: Elsevier
DOI: 10.2139/ssrn.4494030

Sphinx-in-the-Head: Group Signatures from Symmetric Primitives

Autori: Liqun Chen, Changyu Dong, Christopher J. P. Newton and Yalan Wang
Pubblicato in: ACM Transactions on Privacy and Security, 2024, ISSN 2471-2566
Editore: Association for Computing Machinery
DOI: 10.1145/3638763

An ML-Aided Reinforcement Learning Approach for Challenging Vehicle Maneuvers

Autori: Dinesh Cyril Selvaraj, Shailesh Hegde, Nicola Amati, Francesco Deflorio and Carla Fabiana Chiasserini
Pubblicato in: IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, ISSN 2379-8904
Editore: IEEE
DOI: 10.1109/TIV.2022.3224656

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