Project description
Protecting the new generation of cars from cybercriminals
Car safety has come a long way. From the first padded dashboard to seat belts and from rear-view cameras to active safety measures such as autonomous emergency braking (AEB), technological advances are picking up speed. Nowadays, cars are becoming smarter and 'greener' through connectivity and artificial intelligence, and cybersecurity is emerging as a new concern able to stop such huge potential for more sustainable safer roads with zero fatality. The EU-funded CARAMEL project is developing cybersecurity solutions for the new generation of cars: i) autonomous cars, ii) 5G connected vehicles, and iii) electromobility. The project applies a proactive method based on artificial intelligence and machine learning techniques to mitigate cybersecurity-originated safety risks on roads. Considering the entire supply chain, CARAMEL aims to introduce innovative anti-hacking intrusion detection/prevention systems for the European automotive industry.
Objective
The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g. to traffic jams or malicious modifications in sensors’ firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians. CARAMEL’s goal is to proactively address modern vehicle cybersecurity challenges applying advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques, and also to continuously seek methods to mitigate associated safety risks.
In order to address cybersecurity considerations for the already here autonomous and connected vehicles, well established methodologies coming from the ICT sector will be adopted, allowing to assess vulnerabilities and potential cyberattack impacts. Although past initiatives and cybersecurity projects related to the automotive industry have reached to security assurance frameworks for networked vehicles, several newly introduced technological dimensions like 5G, autopilots, and smart charging of Electric Vehicles (EVs) introduce cybersecurity gaps, not addressed satisfactorily yet. Considering the entire supply chain of automotive operations, CARAMEL targets to reach to commercial anti-hacking IDS/IPS products for the European automotive cybersecurity and to demonstrate their value through extensive attack and penetration scenarios.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- engineering and technology electrical engineering, electronic engineering, information engineering information engineering telecommunications telecommunications networks mobile network 5G
- social sciences social geography transport electric vehicles
- engineering and technology mechanical engineering vehicle engineering automotive engineering
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences computer and information sciences computer security
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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)
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.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
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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.
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.
IA - Innovation action
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-SU-ICT-2018-2020
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08034 Barcelona
Spain
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Participants (21)
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08034 Barcelona
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60528 Frankfurt Am Main
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28037 Madrid
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80807 Munchen
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2003 NICOSIA
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3800 075 Aveiro
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5616 LZ Eindhoven
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1096 CJ Amsterdam
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1101 NICOSIA
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IG1 4TD London
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1678 Nicosia
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265 04 RIO PATRAS
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Participation ended
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08028 BARCELONA
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8020 Graz
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63225 Langen
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305700 DAEJON
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31214 CHEONAN-SI
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05854 SEOUL
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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.
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.
28037 MADRID
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53113 Bonn
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08100 Mollet Del Valles
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