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

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708).

Deadline for manuscript submissions: 30 April 2019

Special Issue Editors

Guest Editor
Prof. Naveen Chilamkurti

Department of Computer Science and Computer Engineering, La Trobe University, Melbourne, VIC, Australia
Website | E-Mail
Phone: +61 0 9479 1269
Fax: +61 0 9479 3600
Interests: vehicular communications; vehicular cloud computing; Internet of Things; vehicle to grid; security and services in V2I; wireless sensor networks; authentication and security in wireless; co-operative communications; ontology based services in vehicular cloud; wireless communications; intelligent transport systems (ITS); cybersecurity; security in IoT; wireless sensor networks
Guest Editor
Dr. Jordi Mongay Batalla

Internet Technologies and Applications Department, National Institute of Telecommunications; Warsaw University of Technology, Poland
Website | E-Mail
Interests: Internet technologies (radio: 4G and 5G, wired: network services chain, SDN) and applications (Internet of Things, smart cities, multimedia) for the future Internet
Guest Editor
Dr. Ming-Fong Tsai

Department of Electronic Engineering, National United University, Taiwan
Website | E-Mail
Interests: Internet of Things; vehicular communications; multimedia communications

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 350 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

Open AccessArticle 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
Received: 8 August 2018 / Revised: 7 September 2018 / Accepted: 10 September 2018 / Published: 14 September 2018
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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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Open AccessArticle 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
Received: 21 July 2018 / Revised: 14 August 2018 / Accepted: 23 August 2018 / Published: 1 September 2018
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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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