Special Issue "Vehicle Networks: State-of-the-Art and Prospects"

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Network Services and Applications".

Deadline for manuscript submissions: closed (30 June 2019).

Special Issue Editors

Prof. Dr. Naveen Chilamkurti
E-Mail Website
Guest Editor
Department of Computer Science and Computer Engineering, La Trobe University, Melbourne, VIC 3086, Australia
Interests: blockchain; authentication; IoT; fog computing; 5G; cloud security and wireless communications
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jordi Mongay Batalla
E-Mail Website
Guest Editor
Faculty of Electronics and Informatics Technologies, Warsaw University of Technology, Warsaw, Poland
Interests: applications for Future Internet (smart cities, IoT, multimedia); future networks architecture (5G); expert of European blockchain services infrastructure at European Commission, Member of Hyperledger Platform
Special Issues, Collections and Topics in MDPI journals
Dr. Ming-Fong Tsai
E-Mail Website
Guest Editor
Department of Electronic Engineering, National United University, Miaoli 360001, Taiwan
Interests: vehicular communications; multimedia communications; machine learning; deep learning and artificial internet of things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Topics of interest include, but are not limited to:

  1. Advanced data capturing and networking technology for vehicular networks
  2. Data sharing and acceptance of vehicular networks
  3. Advanced security and security issues for vehicular networks
  4. Internet of Things and big data technology for vehicular networks
  5. Economic and management aspects of vehicular networks
  6. Advanced driver assistance systems technology for vehicular networks

Prof. Naveen Chilamkurti
Dr. Jordi Mongay Batalla
Dr. Ming-Fong Tsai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Sensor and Actuator Networks is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Article
Hierarchical Growing Neural Gas Network (HGNG)-Based Semicooperative Feature Classifier for IDS in Vehicular Ad Hoc Network (VANET)
J. Sens. Actuator Netw. 2018, 7(3), 41; https://doi.org/10.3390/jsan7030041 - 14 Sep 2018
Cited by 7 | Viewed by 5071
Abstract
In this research, new modeling strategy based hierarchical growing neural gas network (HGNG)-semicooperative for feature classifier of intrusion detection system (IDS) in a vehicular ad hoc network (VANET). The novel IDS mainly presents a new design feature for an extraction mechanism and a [...] Read more.
In this research, new modeling strategy based hierarchical growing neural gas network (HGNG)-semicooperative for feature classifier of intrusion detection system (IDS) in a vehicular ad hoc network (VANET). The novel IDS mainly presents a new design feature for an extraction mechanism and a HGNG-based classifier. Firstly, the traffic flow features and vehicle location features were extracted in the VANET model. In order to effectively extract location features, a semicooperative feature extraction is used for collecting the current location information for the neighboring vehicles through a cooperative manner and the location features of the historical location information. Secondly, the HGNG-based classifier was designed for evaluating the IDS by using a hierarchy learning process without the limitation of the fix lattice topology. Finally, an additional two-step confirmation mechanism is used to accurately determine the abnormal vehicle messages. In the experiment, the proposed IDS system was evaluated, observed, and compared with the existing IDS. The proposed system performed a remarkable detection accuracy, stability, processing efficiency, and message load. Full article
(This article belongs to the Special Issue Vehicle Networks: State-of-the-Art and Prospects)
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Article
Bring Your Own Reputation: A Feasible Trust System for Vehicular Ad Hoc Networks
J. Sens. Actuator Netw. 2018, 7(3), 37; https://doi.org/10.3390/jsan7030037 - 01 Sep 2018
Cited by 9 | Viewed by 4581
Abstract
The establishment of trust in vehicular ad hoc networks (VANETs) will require the application of non-conventional measures of information security, such as reputation of the participants. The system proposed in this paper uses the concept of certified reputation, in which vehicles communicate providing [...] Read more.
The establishment of trust in vehicular ad hoc networks (VANETs) will require the application of non-conventional measures of information security, such as reputation of the participants. The system proposed in this paper uses the concept of certified reputation, in which vehicles communicate providing digital certificates that include their own reputation level. The vehicles periodically come in contact with certification and traffic control authorities to update their reputation levels, which are determined by the validation of their behavior on the network. Decision-making mechanisms in the receiver vehicles are responsible for evaluating whether the messages are true or false, based on the reputation of the communication nodes. The quantitative analysis of simulated scenarios showed the combination of the central reputation scheme with an appropriate vehicular decision mechanism achieved a total of correct decisions superior than without reputation systems. Considering the constraints of a high mobile network, the proposed system is a feasible way to reduce the risk of anomalous or malicious behavior in a vehicular network. Full article
(This article belongs to the Special Issue Vehicle Networks: State-of-the-Art and Prospects)
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