Towards Faster Big Data Analytics for Anti-Jamming Applications in vehicular ad-hoc network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F21%3A00121319" target="_blank" >RIV/00216224:14330/21:00121319 - isvavai.cz</a>
Result on the web
<a href="https://onlinelibrary.wiley.com/doi/full/10.1002/ett.4280" target="_blank" >https://onlinelibrary.wiley.com/doi/full/10.1002/ett.4280</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/ett.4280" target="_blank" >10.1002/ett.4280</a>
Alternative languages
Result language
angličtina
Original language name
Towards Faster Big Data Analytics for Anti-Jamming Applications in vehicular ad-hoc network
Original language description
Nowadays, Wireless Vehicular Ad-Hoc Network (VANET) has become a valuable asset for transportation systems. However, this advanced technology is characterized by highly distributed and networked environment, which makes VANET communications vulnerable to malicious jamming attacks. Although Big Data Analytics has been used to solve this critical security issue by supporting the development of anti-jamming applications, as the amount of vehicular data is growing exponentially, the anti-jamming applications face many challenges (i.e, reactions in real-time) due to the lack of specific solutions that can keep up with the fast advancement of VANET. In this paper, we propose a new vehicular data prioritization model based on coresets to accelerate the Big Data Analytics in VANET. Our experimental evaluation shows that our solution can significantly increase the efficiency for clustering in jamming detection while keeping and improving the clustering quality. Also, the proposed solution can enable the real-time detection and be integrated to anti-jamming applications.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
<a href="/en/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Transactions on Emerging Telecommunications Technologies
ISSN
2161-3915
e-ISSN
2161-3915
Volume of the periodical
32
Issue of the periodical within the volume
10
Country of publishing house
GB - UNITED KINGDOM
Number of pages
18
Pages from-to
1-18
UT code for WoS article
000640572600001
EID of the result in the Scopus database
2-s2.0-85104284359