Cyber-resilient Routing for Internet of Vehicles Networks During Black Hole Attack

Tabassum, Mehnaz; Oliveira, Aurenice M.

doi:10.5815/ijwmt.2022.04.01

Cited by 4 publications

(3 citation statements)

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“…Additionally, various hole attacks [ 57 , 61 ] such as blackhole, sinkhole, wormhole, and greyhole, exploit network protocols to disrupt the routing of packets, leading to information loss or delay. GPS deception attacks [ 62 ], masquerading attacks [ 56 ], wormhole attacks [ 61 ], cookie theft attacks [ 63 ], channel interference attacks [ 62 ], and route modification attacks [ 56 ] gave become even more cunning and deceitful at the application layer, which interfaces directly with the user. Injection attacks [ 61 ] compromise the system by inserting malicious data into a stream of legitimate data.…”

Section: Vehicular Network: Backgroundmentioning

confidence: 99%

Investigation of Security Threat Datasets for Intra- and Inter-Vehicular Environments

Haddaji,

Ayed,

Chaari Fourati

et al. 2024

Sensors

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Vehicular networks have become a critical component of modern transportation systems by facilitating communication between vehicles and infrastructure. Nonetheless, the security of such networks remains a significant concern, given the potential risks associated with cyberattacks. For this purpose, artificial intelligence approaches have been explored to enhance the security of vehicular networks. Using artificial intelligence algorithms to analyze large datasets can enable the early identification and mitigation of potential threats. However, developing and testing effective artificial-intelligence-based solutions for vehicular networks necessitates access to diverse datasets that accurately capture the various security challenges and attack scenarios in this context. In light of this, the present survey comprehensively examines the vehicular network environment, the associated security issues, and existing datasets. Specifically, we begin with a general overview of the vehicular network environment and its security challenges. Following this, we introduce an innovative taxonomy designed to classify datasets pertinent to vehicular network security and analyze key features of these datasets. The survey concludes with a tailored guide aimed at researchers in the vehicular network domain. This guide offers strategic advice on selecting the most appropriate datasets for specific research scenarios in the field.

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Section: Vehicular Network: Backgroundmentioning

confidence: 99%

Investigation of Security Threat Datasets for Intra- and Inter-Vehicular Environments

Haddaji,

Ayed,

Chaari Fourati

et al. 2024

Sensors

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“…The aim of connected and autonomous vehicles is to improve traffic flow, reduce fatalities on the road, and reduce the environmental impact of modern mobility, among others [1]. Vehicle-to-Everything (V2X) communication enables the sharing of various types of information (such as traffic, safety and entertainment) with other vehicles, infrastructures and pedestrians using the road through wired and wireless networks.…”

Section: Introductionmentioning

confidence: 99%

“…In order to facilitate minimum latency V2X communications, 3GPP release version 15 added two additional sidelink transmission modes, Mode 3, and Mode 4 (shown in Figure 1) [7]. In addition to C-V2X Modes 3 and 4, two more sidelink resource allocation NR Modes (1,2) are now available. In the Release 16 by 3GPP, Mode 1 refers to the network-controlled allocation of Radio Resources (RR)s for sidelink communications.…”

Section: Introductionmentioning

confidence: 99%

NR Sidelink Performance Evaluation for Enhanced 5G-V2X Services

Tabassum,

Bastos,

Oliveira

et al. 2023

Vehicles

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The Third Generation Partnership Project (3GPP) has specified Cellular Vehicle-to-Everything (C-V2X) radio access technology in Releases 15–17, with an emphasis on facilitating direct communication between vehicles through the interface, sidelink PC5. This interface provides end-to-end network slicing functionality together with a stable cloud-native core network. The performance of direct vehicle-to-vehicle (V2V) communications has been improved by using the sidelink interface, which allows for a network infrastructure bypass. Sidelink transmissions make use of orthogonal resources that are either centrally allocated (Mode 1, Release 14) or chosen by the vehicles themselves (Mode 2, Release 14). With growing interest in connected and autonomous vehicles, the advancement in radio access technologies that facilitate dependable and low-latency vehicular communications is becoming more significant. This is especially necessary when there are heavy traffic conditions and patterns. We thoroughly examined the New Radio (NR) sidelink’s performance based on 3GPP Releases 15–17 under various vehicle densities, speeds, and distance settings. Thus, by evaluating sidelink’s strengths and drawbacks, we are able to optimize resource allocation to obtain maximum coverage in urban areas. The performance evaluation was conducted on Network Simulator 3 (NS3.34/5G-LENA) utilizing various network metrics such as average packet reception rate, throughput, and latency.

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