Lightweight Secure Authentication and Key Distribution Scheme for Vehicular Cloud Computing

Goumidi, Hadjer; Harous, Saad; Aliouat, Zibouda; Guéroui, Abdelhak Mourad

doi:10.3390/sym13030484

Cited by 10 publications

(3 citation statements)

References 34 publications

(65 reference statements)

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“…In [21], The NTRU cryptosystem was patented by NTRU Cryptosystems. In the proposed system, NTRU has been used for node authentication and to prevent the network from fake nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

Detecting and Preventing False Nodes and Messages in Vehicular Ad-Hoc Networking (VANET)

Masood,

Saeed,

Ali

et al. 2023

IEEE Access

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Vehicular ad-hoc network (VANET) is an advanced mobile wireless network. The escalation of equipped vehicles on the road grabs the attention of researchers and is constantly striving to take it further. This type of wireless network infrastructure helps to establish communication between vehicles. Roadside units, sensors, and vehicular nodes are the critical components of our work to protect the vehicular network. This research is focused on detecting and preventing fake vehicular nodes and their messages by applying fake node detection and prevention algorithms and counterfeit message detection and prevention algorithms. In our proposed approach, the fake node detection and prevention algorithms check the node profile after establishing the mesh structure. If the profile attribute named "Pen/Rew" satisfies the condition that should be less than or equal to a threshold value (zero), the fake message detection and prevention process starts. The message will be accepted once the situation is satisfied; otherwise, it is declared fake. We utilized ONE (opportunistic network environment) simulator to generate node movement models, route messages between nodes, and visualize mobility and messaging passing in real time. The results indicated that our proposed work perfectly detects and prevents fake nodes and messages.

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“…In [21], The NTRU cryptosystem was patented by NTRU Cryptosystems. In the proposed system, NTRU has been used for node authentication and to prevent the network from fake nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

Detecting and Preventing False Nodes and Messages in Vehicular Ad-Hoc Networking (VANET)

Masood,

Saeed,

Ali

et al. 2023

IEEE Access

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“…In [71] the authors propose an algorithm to ensure VCC security and privacy. They use Pseudo-ID instead of vehicles' real ID to provide conductors' privacy, Identifier-Based Signature mechanism is used to guarantee vehicles' authentication, and Ciphertext-Policy Attribute-Based Encryption (CP-ABE) algorithm is used for key distribution.…”

Section: ) Autonomous Vehicles Cloud Computingmentioning

confidence: 99%

Security and Privacy Issues in Autonomous Vehicles: A Layer-Based Survey

Hataba

Sherif

Mahmoud

et al. 2022

IEEE Open J. Commun. Soc.

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Artificial Intelligence (AI) is changing every technology we are used to deal with. Autonomy has long been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Big auto manufacturers as well are investing billions of dollars to produce Autonomous Vehicles (AVs). This new technology has the potential to provide more safety for passengers, less crowded roads, congestion alleviation, optimized traffic, fuel-saving, less pollution as well as enhanced travel experience among other benefits. But this new paradigm shift comes with newly introduced privacy issues and security concerns. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected. They collect huge troves of information, which needs to be protected from breaches. In this work, we investigate security challenges and privacy concerns in AVs. We examine different attacks launched in a layer-based approach. We conceptualize the architecture of AVs in a four-layered model. Then, we survey security and privacy attacks and some of the most promising countermeasures to tackle them. Our goal is to shed light on the open research challenges in the area of AVs as well as offer directions for future research.

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“…In recent years, the emergence of the Internet of Vehicles (IoVs) enables huge potential in the area of intelligent transportation [23][24][25][26][27][28][29][30][31]. It mainly includes vehicle-to-vehicle (V2V), vehicle-to-road (V2R), vehicle-to-infrastructure (V2I) and so on.…”

Section: Introductionmentioning

confidence: 99%

Predictive Intelligent Transportation: Alleviating Traffic Congestion in the Internet of Vehicles

Zhang

Khalgui

2021

Sensors

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Due to the limitations of data transfer technologies, existing studies on urban traffic control mainly focused on isolated dimension control such as traffic signal control or vehicle route guidance to alleviate traffic congestion. However, in real traffic, the distribution of traffic flow is the result of multiple dimensions whose future state is influenced by each dimension’s decisions. Presently, the development of the Internet of Vehicles enables an integrated intelligent transportation system. This paper proposes an integrated intelligent transportation model that can optimize predictive traffic signal control and predictive vehicle route guidance simultaneously to alleviate traffic congestion based on their feedback regulation relationship. The challenges of this model lie in that the formulation of the nonlinear feedback relationship between various dimensions is hard to describe and the design of a corresponding solving algorithm that can obtain Pareto optimality for multi-dimension control is complex. In the integrated model, we introduce two medium variables—predictive traffic flow and the predictive waiting time—to two-way link the traffic signal control and vehicle route guidance. Inspired by game theory, an asymmetric information exchange framework-based updating distributed algorithm is designed to solve the integrated model. Finally, an experimental study in two typical traffic scenarios shows that more than 73.33% of the considered cases adopting the integrated model achieve Pareto optimality.

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Lightweight Secure Authentication and Key Distribution Scheme for Vehicular Cloud Computing

Cited by 10 publications

References 34 publications

Detecting and Preventing False Nodes and Messages in Vehicular Ad-Hoc Networking (VANET)

Detecting and Preventing False Nodes and Messages in Vehicular Ad-Hoc Networking (VANET)

Security and Privacy Issues in Autonomous Vehicles: A Layer-Based Survey

Predictive Intelligent Transportation: Alleviating Traffic Congestion in the Internet of Vehicles

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