Challenges in Designing Ethical Rules for Infrastructures in Internet of Vehicles

Iqbal, Razi

doi:10.14569/ijacsa.2018.090303

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…The aim is to efficiently operate routing, healthcare applications, 9 mobility management, 10,11 military applications, 12 safety alarms, 13 data dissemination, 14 and Internet connectivity. 15 This topic will continue to remain generally there for another few years. We believe to have greater exploration in near future in the core topic of clustering algorithms, analysis, comparison as well as evaluation of clustering algorithms, preparation of simulation statistics and so on.…”

Section: Introductionmentioning

confidence: 99%

Intelligent clustering using moth flame optimizer for vehicular ad hoc networks

Ishtiaq

Ahmed

Khan

et al. 2019

International Journal of Distributed Sensor Networks

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Vehicular ad hoc networks consist of access points for communication, transmission, and collecting information of nodes and environment for managing traffic loads. Clustering can be performed in the vehicular ad hoc networks for achieving the desired goals. Due to the random range of vehicular ad hoc networks, stability is the major issue on which major research is still in progress. In this article, a moth flame optimization-driven clustering algorithm is presented for vehicular ad hoc networks, replicating the social behavior of moth flames in creating efficient clusters. The proposed framework is extracted from the living routine of moth flames. The proposed framework allows efficient communication by creating the augmented number of clusters due to which it is termed as intelligent algorithm. Besides this, the use of unsupervised clustering technique emphasizes to call it as an intelligent clustering algorithm. The recommended intelligent clustering using moth flame optimization framework is executed for resolving and optimizing the clustering problem in vehicular ad hoc networks, the primary focus of the proposed scheme is to improve the stability in vehicular ad hoc networks. This proposed method can also be used for the transmission of data in vehicular networks. Intelligent clustering using moth flame optimization is then proved by relative study with two variants of particle swarm optimization: multiple-objective particle swarm optimization and comprehensive learning particle swarm optimization and a variant of ant colony optimization: ant colony optimization-based clustering algorithm for vehicular ad hoc network. The simulation demonstrates that the intelligent clustering using moth flame optimization is provisioning optimal outcomes in contrast to widely known metaheuristics. Furthermore, it provides a robust routing mechanism based on the clustering. It is suitable for large highways for the productivity of quality communication, reliable delivery for each vehicle and can be widely applicant.

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Section: Introductionmentioning

confidence: 99%

Intelligent clustering using moth flame optimizer for vehicular ad hoc networks

Ishtiaq

Ahmed

Khan

et al. 2019

International Journal of Distributed Sensor Networks

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A Service of RSU Communication in Internet of Vehicles (IoV) in Urban Environment

Al-Essa

Al–Suhail

2023

Lecture Notes in Networks and Systems

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MARINE: Man-in-the-Middle Attack Resistant Trust Model in Connected Vehicles

Ahmad

Kurugöllü

Adnane

et al. 2020

IEEE Internet Things J.

118

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Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.

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Challenges in Designing Ethical Rules for Infrastructures in Internet of Vehicles

Cited by 3 publications

References 15 publications

Intelligent clustering using moth flame optimizer for vehicular ad hoc networks

Intelligent clustering using moth flame optimizer for vehicular ad hoc networks

A Service of RSU Communication in Internet of Vehicles (IoV) in Urban Environment

MARINE: Man-in-the-Middle Attack Resistant Trust Model in Connected Vehicles

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