Cybersecurity of Sensors on Smart Vehicles: Review of Threats and Solutions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F23%3A39921212" target="_blank" >RIV/00216275:25530/23:39921212 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10331330" target="_blank" >https://ieeexplore.ieee.org/document/10331330</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IC2IE60547.2023.10331330" target="_blank" >10.1109/IC2IE60547.2023.10331330</a>
Alternative languages
Result language
angličtina
Original language name
Cybersecurity of Sensors on Smart Vehicles: Review of Threats and Solutions
Original language description
The use of sensors in smart vehicles brings benefits and vulnerabilities. Different kinds of sensors in smart vehicles are vulnerable to cyber-attack. Until now, theinvestigation of challenges and solutions for in-vehicle cybersecurity hasn’t discussed various sensor objects and their correlation. In this study, we studied the cyber securityproblems of sensors in smart vehicles and how to overcome them. The research was designed as Systematic Literature Review (SLR) using the Kitchenham methodology with modification in the filtering phase using the artificial intelligence application, Elicit, to identify the problems, conclusions, and methodology description. Seventeenpublications from 2016 until 2023 were gained from five databases. As a result, we find that the most discussed object related to cybersecurity sensors on smart vehicles areElectronic Control Units. Spoofing and jamming is still the most addressed threat, and machine learning is the most utilized solution to be implemented in detection systems.Advanced detection systems are incorporating updated attack models. We also suggest using updated attack models and machine learning algorithms to ensure the safety and security of smart vehicle technology. All identified sensor technology correlated using mind maps under the Intelligent Transport System theory.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings - 2023 6th International Conference on Computer and Informatics Engineering: AI Trust, Risk and Security Management (AI Trism), IC2IE 2023
ISBN
979-8-3503-4517-9
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
266-270
Publisher name
IEEE (Institute of Electrical and Electronics Engineers)
Place of publication
New York
Event location
Lombok
Event date
Sep 14, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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