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General Information
ISSN:
1796-2021 (Online); 2374-4367 (Print)
Abbreviated Title:
J. Commun.
Frequency:
Monthly
DOI:
10.12720/jcm
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Acceptance Rate:
27%
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800 USD
Average Days to Accept:
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3.4
2023
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Editor-in-Chief
Prof. Maode Ma
College of Engineering, Qatar University, Doha, Qatar
I'm very happy and honored to take on the position of editor-in-chief of JCM, which is a high-quality journal with potential and I'll try my every effort to bring JCM to a next level...
[Read More]
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2024-11-25
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Home
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2019
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Volume 14, No. 5, May 2019
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VANET Blockchain: A General Framework for Detecting Malicious Vehicles
Ahmad Mostafa
Computer Networks Department Faculty of Informatics and Computer Science The British University in Egypt
Abstract
—Malicious nodes are affecting many of the current networks, specially, the decentralized networks such as VANETs. VANETs are highly decentralized networks that are highly dynamic and include many nodes or vehicles that are introduced and leave the network abruptly. In order to overcome this challenge, we propose using the blockchain technology. Blockchain is an emerging technology that is changing how modern system and technologies operate. Many systems nowadays are based on this technology including the Bitcoin system. However, many other technologies are realizing the potential benefits of the blockchain technology. In this paper, we propose the use of mini blockchain in the detection of malicious vehicles in VANET. We propose a general framework in which malicious vehicles will not be able to gain the trust of other vehicles and be part of the network. This is achieved through the utilization of environmental sensory data and validating the authenticity of the packets, and allowing a vehicle to add different blocks to the blockchain. We show that our framework is able to deal with malicious nodes and with Sybil attacks.
Index Terms
—VANET, blockchain, sybil attacks, authentication, data validation, mini blockchain, fingerprint, malicious nodes
Cite: Ahmad Mostafa, "VANET Blockchain: A General Framework for Detecting Malicious Vehicles," Journal of Communications, vol. 14, no. 5, pp. 356-362, 2019. Doi: 10.12720/jcm.14.5.356-362
4-NT015
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