Security assessment in Vehicle-to-Everything communications with the integration of 5G and 6G networks

Khan, Shah Khalid; Shiwakoti, Nirajan; Stasinopoulos, Peter; Warren, Matthew

doi:10.1109/iscsic54682.2021.00037

Cited by 11 publications

(5 citation statements)

References 26 publications

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“…Another meaningful direction is to integrate traffic knowledge into Machine Learning models for cyberattack detection/prediction and proactive defence. Last but not the least, the proposed cyberattacks should be further evaluated using more security performance metrics, such as availability, authentication, reliability, confidentiality, integrity, robustness and trustworthiness [49]. More results and findings will be provided in the subsequent publications.…”

Section: Discussionmentioning

confidence: 99%

Cyberattacks on connected automated vehicles: A traffic impact analysis

Sun

Liu

et al. 2022

IET Intelligent Trans Sys

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Cybersecurity has become one of the major challenges for Connected Automated Vehicles. Previous work in this field mostly focused on the detection of and defence against Connected Automated Vehicle‐related cyberattacks. Using performance measures collected from traffic micro‐simulations, the study analysed the traffic impacts of cyberattacks on Connected Automated Vehicles. Two types of adversary models, namely, time‐delay attacks and disturbance attacks, were applied to the simulated traffic on freeway segments and un‐signalised intersections, respectively. The effects of various cyberattacks were evaluated based on safety indicators, including Time‐To‐Collision, Deceleration Rate to Avoid Collision, and efficiency indicators, including speed and flow‐density diagrams. The results revealed that both attacks increase the risk and severity of collisions on freeway segments and un‐signalised intersections. Location‐based time‐delay attacks will result in significant deceleration, congestion and reduction in road throughput. Disturbance attacks not only cause congestion but also result in frequent acceleration/deceleration and uneven distribution of traffic density. The impacts of attacks are more severe on heavy traffic. At un‐signalised intersections, location‐based disturbance attacks lead to a significantly increased risk of right‐angled collisions. The results could help better understand the effects of Connected Automated Vehicle‐related cyberattacks and shed light on proactive defence against such attacks.

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Section: Discussionmentioning

confidence: 99%

Cyberattacks on connected automated vehicles: A traffic impact analysis

Sun

Liu

et al. 2022

IET Intelligent Trans Sys

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“…The study [24] is a security assessment of V2X integration with 6G networks. However, it does not systematically cover the complete security architecture such as countermeasures and intrusion detection systems etc.…”

Section: A Related Previous Surveys / Reviews In the Literaturementioning

confidence: 99%

Security of 6G-Enabled Vehicle-to-Everything Communication in Emerging Federated Learning and Blockchain Technologies

Kim,

Oh,

Yim

et al. 2024

IEEE Access

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Sixth-generation (6G) communication is emerging as seamless and massive connecting of almost everything. Therefore, vehicles, being extensively linked with human mobility, require a technological pace for compatibility with the 6G era. 6G will also potentially revolutionize the Vehicle-to-Everything (V2X) communication. However, this modernization will surface several security challenges in the complex heterogeneous architecture of V2X communication in 6G. Similarly, the expansion of V2X also introduces unconventional security risks and vulnerabilities. This paper aims to provide an overview of the security challenges and solutions for V2X communication in the upcoming 6G era to visualize the future of this research domain. This paper discusses the architecture and standards utilized in 6G enabled V2X communications and provisions a comprehensive analysis of V2X security in Confidentiality, Integrity, Availability, Authentication and Access Control (CIA 3 ) domains. Thereby, we analyze the impact of the emerging technological concepts of Blockchain and Federated Learning (FL) in 6G enabled V2X communication. Thereby, we suggest a Blockchain-enabled FL based generic security architecture for V2X communication in 6G networks. At the conclusive end, the review highlights key lessons learned and the future research directions in the domain of security of V2X communications in the 6G including; Privacy in 3D Fog Computing, Privacy in Augmented Reality, C. Secure Software Defined Networking (SDN), Physical Layer Security In THz Spectrum, SUMO (Simulation of Urban MObility) and Intrusion Detection using AI.

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“…The authors in [8] offer a security assessment for the evolution of Vehicle-to-Everything Communications (V2X-C) architecture and the integration of 5G and 6G networks. They also provide a comparison of the Quality of Service (QoS) versus security provisions for Connected and AV (CAVs) and illustrate the safety and security enhancement mechanisms for V2X-C. A deep CNN-LSTM architecture is proposed in [9] for CAV intelligence threats and compared with other deep learning algorithms such as DNN, CNN, and LSTM.…”

Section: Literature Reviewmentioning

confidence: 99%

Autonomous Vehicles With a 6G-Based Intelligent Cybersecurity Model

Algarni

Thayananthan

2023

IEEE Access

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Sixth-generation (6G)-based communications have many applications and are emerging as a new system to utilize existing vehicles and communication devices in autonomous vehicles (AVs). Electric vehicles and AVs not supporting the integration of intelligent cybersecurity will become vulnerable, and their internal functions, features, and devices providing services will be damaged. This paper presents an intelligent cybersecurity model integrating intelligent features according to the emerging 6G-based technology based on evolving cyberattacks. The model's novel design was developed using the necessary algorithms to provide quick and proactive decisions with intelligent cybersecurity based on 6G (IC6G) policies when AVs face cyberattacks. In this model, network security algorithms incorporating intelligent techniques are developed using applied cryptography. Money transaction handling services implemented in an AV are considered an example to determine the security and intelligence level depending on the IC6G policies. Intelligence, complexity, and energy efficiency (EE) are assessed. Finally, we conclude that the model results are effective for intelligently detecting and preventing cyberattacks on AVs.

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Security assessment in Vehicle-to-Everything communications with the integration of 5G and 6G networks

Cited by 11 publications

References 26 publications

Cyberattacks on connected automated vehicles: A traffic impact analysis

Cyberattacks on connected automated vehicles: A traffic impact analysis

Security of 6G-Enabled Vehicle-to-Everything Communication in Emerging Federated Learning and Blockchain Technologies

Autonomous Vehicles With a 6G-Based Intelligent Cybersecurity Model

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