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UBITECH’s paper on automated privacy and security risk assessment published at the MDPI Future Internet online journal

The paper entitled “A Perfect Match: Converging and Automating Privacy and Security Impact Assessment On-the-Fly” has been accepted and published online at the Special Issue “Information and Future Internet Security, Trust and Privacy” of the Future Internet (ISSN 1999-5903), an open access journal published monthly online by MDPI. The UBITECH’s Digital Security and Trusted Computing research group proposes the APSIA methodology, which stands for Automated Privacy and Security Impact Assessment. APSIA is powered by the use of interdependency graph models and data processing flows used to create a digital reflection of the cyber-physical environment of an organisation. Along with this model, we present a novel and extensible privacy risk scoring system for quantifying the privacy impact triggered by the identified vulnerabilities of the ICT infrastructure of an organisation.

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Successful final review for the BigDataStack Research and Innovation Action

After 3 years of an exciting R&D journey, the UBITECH’s Privacy-preserving Distributed Machine Learning research group proudly delivered and integrated the Data Toolkit and the Information-driven Networking Mechanisms in the BigDataStack infrastructure management system. The Data Toolkit and the Information-driven Networking Mechanisms exhibited their applicability in the three use cases related with automated analytic pipelines and software defined networking mechanisms for real-time ship management, connected consumer and smart insurance applications. The BigDataStack project (Grant Agreement No 779747) had a successful final – virtual – review by the European Commission on the 27th of January 2021. We are happy to be part of such an enthusiastic team and sad that the BigDataStack project is over! BigDataStack delivers a complete pioneering stack that drives decisions according to data aspects based on current and past application and infrastructure deployments. Therefore, the BigDataStack infrastructure management system is scalable and adaptable at runtime, able to address the emerging needs of big data operations and data-intensive applications.

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Successful interim review for the SDN-microSENSE H2020 Innovation Action on Electrical Energy Systems Cybersecurity

The first contractual virtual review meeting for the SDN-microSENSE H2020 Innovation Action co-funded research project (https://www.sdnmicrosense.eu/) with external reviewers and the Project Officer from the EC side took place on January 26, 2021, wherein the SDN-microSENSE consortium successfully presented the results of the work of the project during the first 20 months of the project. The SDN-microSENSE project intends to provide a set of secure, privacy-enabled and resilient to cyberattacks tools, thus ensuring the normal operation of Electrical Power and Energy Systems (EPES) as well as the integrity and the confidentiality of communications. UBITECH presented the 2nd Objective of the project related to the SDN-microSENSE Risk Assessment Framework (S-RAF) which includes iterative risk and vulnerability assessments on existing energy value chain assets including processes and personnel. The reviewers and the Project Officer were satisfied with the results and provided some feedback and recommendations for the future work. The SDN-microSENSE consortium is enthusiastic about continuing their work in the project.

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UBITECH’s co-authored scientific paper on Data-Intensive Multi-Cloud, Fog, and Edge Function-as-a-Service Applications published at IRMJ

The scientific paper entitled “PrEstoCloud: A Novel Framework for Data-Intensive Multi-Cloud, Fog, and Edge Function-as-a-Service Applications”, co-authored by UBITECH, has been accepted and published online at the Information Resources Management Journal (IRMJ) of IGI Global. Giannis Ledakis, Head of UBITECH’s Computing Systems, Software and Services research group, and his co-authors from NTUA and JSI review prominent fog computing frameworks and discuss some of the challenges and requirements of Function-as-a-Service (FaaS) -enabled applications. Moreover, they propose a novel framework able to dynamically manage multi-cloud, fog, and edge resources and to deploy data-intensive applications developed using the FaaS paradigm. The proposed framework leverages the FaaS paradigm in a way that improves the average service response time of data-intensive applications by a factor of three regardless of the underlying multi-cloud, fog, and edge resource infrastructure.

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UBITECH undertakes the integration lead of the inGOV Research and Innovation Action on Inclusive Governance Models and ICT Tools for Integrated Public Service Co-Creation and Provision

UBITECH participates at the virtual kick-off meeting (January 25-26, 2021), hosted by UniSystems, of the inGOV Research and Innovation Action, officially started on January 1st, 2021. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 962563) and spans on the period January 2021 – December 2023. The vision of inGOV project is to enable European public authorities to co-create user-friendly, integrated public services accessible via mobile devices to all, particularly the disadvantaged, resulting in increased adoption, efficiency, effectiveness, trust and satisfaction – supporting the Integrated Public Service (IPS) cocreation.

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UBITECH undertakes the technical coordination of the 5G-INDUCE Innovation Action on open cooperative 5G experimentation platforms for the industrial sector NetApps

UBITECH co-hosts (along with CNIT) the virtual kick-off meeting (January 20-21, 2021) of the 5G-INDUCE Innovation Action, officially started on January 1st, 2021. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 101016941) and spans on the period January 2021 – December 2023. The vision of 5G-INDUCE aims to support vertical stakeholders and NetApp developers to be able to smoothly deploy and manage applications in distributed 5G network environments, in a secure fashion and with strict KPI requirements. 5G-INDUCE relies on the deployment of an open ETSI NFV compatible 5G orchestration platform for the deployment of advanced 5G NetApps.

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UBITECH kicks off the DataCloud Research and Innovation Action on Big Data Pipeline Lifecycle Management across the Computing Continuum

UBITECH participates at the virtual kick-off meeting hosted by SINTEF (January 19-21, 2021) of the DataCloud Research and Innovation Action, officially started on January 1st, 2021. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 101016835) and spans on the period January 2021 – December 2023. The DataCloud project provides a novel paradigm covering the complete lifecycle of managing Big Data pipelines through discovery, design, simulation, provisioning, deployment, and adaptation across the Computing Continuum. Big Data pipelines in DataCloud interconnect the end-to-end industrial operations of collecting pre-processing and filtering data, transforming and delivering insights, training simulation models, and applying them in the cloud to achieve a business goal. DataCloud delivers a toolbox of new languages, methods, infrastructures, and prototypes for discovering, simulating, deploying, and adapting Big Data pipelines on heterogeneous and untrusted resources. DataCloud separates the design from the run-time aspects of Big Data pipeline deployment, empowering domain experts to take an active part in their definitions.

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UBITECH kicks off the TeraFlow Research and Innovation Action on Secured Autonomic Traffic Management for a Tera of SDN flows

UBITECH participates at the virtual kick-off meeting hosted by CTTC (January 19-20, 2021) of the TeraFlow Research and Innovation Action, officially started on January 1st, 2021. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 101015857) and spans on the period January 2021 – June 2023. The TeraFlow project aims to create a new type of secure cloud native SDN controller that will radically advance the state-of-the-art in beyond 5G networks. This new SDN controller shall be able to integrate with the current NFV and MEC frameworks as well as to provide revolutionary features for both flow management (service layer) and optical/microwave network equipment integration (infrastructure layer), while incorporating security using Machine Learning (ML) and forensic evidence for multitenancy based on Distributed Ledgers.

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UBITECH ENERGY kicks off the SMART5GRID Innovation Action on the demonstration of 5G solutions for Smart Energy Grids

UBITECH ENERGY participates at the virtual kick-off meeting hosted by ENEL (January 19-21, 2021) of the Smart5Grid Innovation Action, officially started on January 1st, 2021. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 101016912) and spans on the period January 2021 – December 2023. The Smart5Grid project aims to revolutionise the Energy industry through the successful establishment of four fundamental functions of modern smart grids, i.e., (i) automatic power distribution grid fault detection, (ii) remote inspection of automatically delimited working areas, (iii) millisecond level precise distribution generation control, and (iv) real-time wide area monitoring in a creative cross-border scenario, thus assisting power grid operators and other energy stakeholders.

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UBITECH kicks off the STAR Research and Innovation Action on Trusted AI in Manufacturing

UBITECH participates at the virtual kick-off meeting hosted by INTRASOFT (January 11-12, 2021) of the STAR Research and Innovation Action, officially started on January 1st, 2021. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 956573) and spans on the period January 2021 – December 2023. The STAR project constitutes a joint effort of AI and digital manufacturing experts towards enabling the deployment of standard-based secure, safe reliable and trusted human centric AI systems in manufacturing environments. STAR will research and make available to novel technologies that will enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, STAR will research technologies that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks.

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