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contINuous deCentralized lEarNing of ioT devIces' behaVioural profilEs

Objective

In an increasingly hyperconnected society, cybersecurity concerns take on a broader dimension, which can impact citizens safety. This has been widely recognized in the EU through specific legal instruments, such as the Cybersecurity Act and the recent Cybersecurity Strategy for the Digital Decade. The development of the IoT technologies have fostered the deployment of data-driven services for everyday scenarios, such as transport, health and energy, but have also increased the probability and impact of new cybersecurity threats. Recent and well-known attacks have demonstrated the need to develop AI-based techniques to identify such attacks in IoT scenarios. In this context, the objective of this project is to build a decentralized framework to learn the IoT devices intended behavior throughout their lifecycle, in order to distinguish abnormal behavior that may reflect a security attack or threat. The proposal will build an edge-based and federated learning architecture to enable IoT devices to participate in the learning process by using lightweight security protocols. This architecture will include the use of blockchain through a novel approach in which different ledgers will be interconnected to improve the performance and practicability of existing approaches. Furthermore, the proposal will be the first effort to quantify the impact of human-machine interactions on the devices intended behavior. The project will be validated quantitatively and qualitatively to identify potential tradeoffs for its deployment in different IoT-enabled scenarios. It will leverage the candidates extensive knowledge and experience in IoT cybersecurity, which will be strengthened by the host institution to improve his technical and transferable skills in a multidisciplinary environment. The proposed project represents a unique contribution to reinforcing the culture of cybersecurity in the EU that will boost the candidate's professional development during and after the fellowship.

Fields of science (EuroSciVoc)

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-MSCA-2021-PF-01

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Coordinator

UNIVERSIDAD DE MURCIA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 181 152,96
Address
AVENIDA TENIENTE FLOMESTA S/N - EDIFICIO CONVALECENCIA
30003 Murcia
Spain

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Region
Sur Región de Murcia Murcia
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Partners (2)

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