Project description
Cybersecurity considerations for self-driving cars
The rise of connectivity and automation technology is creating more and more opportunities in many fields. Connected and autonomous vehicles (CAV) is a field widely affected by these technology advancements. While innovation is disrupting business standards and encouraging investments, it is also at risk of cybersecurity attacks. The EU-funded MALAGA project will use machine learning (ML) technology to investigate cybersecurity risks, as well as find ways to reduce risks in the CAV field. With ML, the project will predict risks and price insurance policies to pave the way for innovation and entrepreneurial activity in Europe.
Objective
Increasing connectivity and automation presents many opportunities and challenges for society. Emerging technology can benefit all citizens with better communication, increased environmental sustainability, autonomous transport, safer roads,, the list is almost inexhaustible. These emerging technologies will disrupt existing business models including underwriting and risk transfer. This disruption can stifle venture capital, innovation and risk taking in key emerging technologies and can inhibit regulatory development and societal acceptance.
My research will examine Connected and Autonomous Vehicles (CAV) cybersecurity risks and mitigation using Machine Learning (ML) techniques to predict future risks, price insurance policies and and thereby foster innovation and entrepreneurial activity in Europe. My research will go beyond the SoA and implement models in ML like ensemble models and deep learning to forecast the risks of CAV technology. A network model of interactions will be trained and evaluated to study cascading of risks and threats in the CAV environment.
My host team at the University of Limerick have members with machine learning skills, actuarial skills, ethical skills and underwriting experience. I will have access to staff development programmes, training courses, workshops, online courses and internal meetings. My host team are directly connected to a large variety of colleagues in other EU locations in both academic and industry positions. I will work with my host and partners to develop my research and increase my skillsets.
My research directly contributes to several UN sustainable development goals. On a personal level, the impact of my fellowship and collaborations will expand my set of skills, both research-related and transferable ones, leading to greatly improved career prospects both in and outside academia. My new abilities will include enhanced machine learning capabilities, cyber risk expertise and risk engineering skills.
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: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology mechanical engineering vehicle engineering automotive engineering autonomous vehicles
- social sciences sociology industrial relations automation
- social sciences economics and business business and management business models
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- 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.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
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.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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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-MSCA-IF-2018
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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.
- Limerick
Ireland
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.