Name: Fostering Mutual Trust among Edge Devices for Securing the Fog Continuum
Funding_Authority: EU-H2020
Coordinator: UBITECH
Start_Date: 01/01/2021
End_Date: 31/12/2023
Duration(months): 36
UCY_Budget: 352,500
Total_Budget: 5,000,000
Principal_Investigator: Pallis George
Co_principal_Investigator: Dikaiakos Marios


The vision of TrustedFog project is to enable the trustworthiness and sustainability of emerging open fog/edge computing platforms for the connection of devices and objects with dynamically configurable capabilities and the deployment and management of scalable, heterogeneous and secure IoT services and cross-cloud applications. The key innovations rely on a) the introduction of remote attestation processes for providing enhanced operational assurance across the fog environment with the goal to check and assure the integrity of the devices for distributed trust management, b) the deployment of the networking mechanisms that enable secure routing and efficient authorization management at the fog and edge layer, resulting in a secure overlay mesh network for encrypted communication, data protection and established trust among collaborative fog and cross-cloud services, and c) the development of an AI-fuelled resource management and fog service orchestration framework for modelling service constraints, optimization policies and QoS requirements. Demanding real world scenarios (on smart energy Grids, public protection and disaster relief in IoT and drones, remote buildings maintenance and access control) are adopted to evaluate and demonstrate the proposed enabling solutions, showcasing features such as real-time responsiveness, availability, data freshness, efficient data protection and management, and industry-specific security standards. The implementations of TrustedFog developments contribute directly to the growing cybersecurity market, while enabling edge/fog based intelligent service provisioning, which is reported as the fastest growing and most impactful (financially and societally) ICT sector in the upcoming years. The project follows three well-defined implementation phases with two development and integration periods and optimization feedback processes, contributing to the demonstration of the proposed concepts through the three innovative scenarios.

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