Secure Authentication and Key Management Protocol for Deployment of Internet of Vehicles (IoV) Concerning Intelligent Transport Systems

Bojjagani, Sriramulu; Reddy, Y. C. A. Padmanabha; Anuradha, T.; Rao, P. V. Venkateswara; Reddy, B. Ramachandra; Khan, Muhammad Khurram

doi:10.1109/tits.2022.3207593

Cited by 32 publications

(7 citation statements)

References 36 publications

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“…To address integration challenges between various end node devices in an IoT system, Bojjagani et al 17 suggested using a web-based service strategy for IoT service design. They also analyzed the state of the art in terms of the ideas, infrastructure, and solutions that can be used to build IoT-based smart cities.…”

Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: A vehicular network based intelligent transport system for smart cities using machine learning algorithms

Prakash,

Murali,

Manikandan

et al. 2024

Sci Rep

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Smart cities and the Internet of Things have enabled the integration of communicating devices for efficient decision-making. Notably, traffic congestion is one major problem faced by daily commuters in urban cities. In developed countries, specialized sensors are deployed to gather traffic information to predict traffic patterns. Any traffic updates are shared with the commuters via the Internet. Such solutions become impracticable when physical infrastructure and Internet connectivity are either non-existent or very limited. In case of developing countries, no roadside units are available and Internet connectivity is still an issue in remote areas. Internet traffic analysis is a thriving field of study due to the myriad ways in which it may be put to practical use. In the intelligent Internet-of-Vehicles (IOVs), traffic congestion can be predicted and identified using cutting-edge technologies. Using tree-based decision-tree, random-forest, extra-tree, and XGBoost machine learning (ML) strategies, this research proposes an intelligent-transport-system for the IOVs-based vehicular network traffic in a smart city set-up. The suggested system uses ensemble learning and averages the selection of crucial features to give high detection accuracy at minimal computational costs, as demonstrated by the simulation results. For IOV-based vehicular network traffic, the tree-based ML approaches with feature-selection (FS) outperformed those without FS. When contrasted to the lowest KNN accuracy of 96.6% and the highest SVM accuracy of 98.01%, the Stacking approach demonstrates superior accuracy as 99.05%.

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Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: A vehicular network based intelligent transport system for smart cities using machine learning algorithms

Prakash,

Murali,

Manikandan

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…By strategically deploying IRS along roadways and within urban environments, we aim to harness their reflective properties to enhance signal propagation, mitigate interference, and bolster the reliability of wireless communication between vehicles and RSUs. The integration of IRS not only holds the promise of extending network coverage to previously inaccessible areas but also opens avenues for optimizing spectrum utilization and reducing energy consumption in IoV deployments [38].…”

Section: Intelligent Reflecting Surface (Irs) Integrationmentioning

confidence: 99%

Enhancing the Internet of Vehicles through Collaborative Cryptographic Mechanisms with IRS

Aljumaili,

Trabelsi,

Jerbi

et al. 2024

icisna

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The Internet of Vehicles (IoV) is transforming transportation systems by allowing for seamless communication and collaboration between vehicles, roadside units (RSUs), and cloud servers. However, the dynamic and varied character of IoV settings raises serious security and efficiency concerns. This work suggests a novel strategy to addressing these issues by combining collaborative cryptographic processes and intelligent reflecting surfaces (IRS). Our method uses modern encryption techniques, such as the modern Encryption Standard (AES), to assure safe data delivery, while intelligent reflecting surfaces dynamically modify their reflection qualities to improve signal propagation and reception. We provide a detailed network model and algorithmic framework for implementing the suggested strategy, with a focus on cryptographic techniques and the role of intelligent reflecting surfaces in improving communication security and efficiency. Through theoretical analysis and debate, we emphasize the possible benefits of incorporating intelligent reflecting surfaces in IoV networks, such as improved network coverage, lower communication costs, and increased energy efficiency. Furthermore, we explore the implications of our strategy for IoV security and suggest future research areas in this area.

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“…The Scyther is one of the most modern testing tools developed as symbols (Cremers) at the Technology Eindhoven University [42] , and it has a graphical interface in which the analysis of security protocols is performed by one click of a button, where these lines include commands that write commands in the Python language [43], in this tool the protocol description and parameters are taken The other is as an entry, and as for an exit, it provides a summary report and displays a diagram for each attack [44]. The figure(2) [45] shows the mechanism of action of this tool.…”

Section: Formal Security Verification Using Scyther Toolmentioning

confidence: 99%

A Robust Privacy Preserving Authentication Scheme for IOT Environment by 5G Technology

Dawood

2024

KJCS

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In recent years, secure communication between the interconnected components of the internet of things has become an important and worrying issue due to some attacks on the IoT. The Internet of Things (IOT) is the integration of things with the world of the Internet, where this integration takes place by adding devices or programs to be smart and, as a result, they will be able to communicate with one another and participate in all elements of life quite efficiently. Accordingly, we've developed an authentication protocol for the IoT ecosystem; it's primary function is to ensure the safety of data exchange between the many devices that make up the IoT. Our proposed protocol is based on the elliptic curve cipher (ECC) algorithm, which greatly aids in protecting IoT components from physical assault. Our informal protocol analysis demonstrates that our solution not only protects users' privacy by concealing their devices' identities but also thwarts impersonation, counterattacks, and tracking and suggestion attacks directed at IoT devices. Security characteristics of the proposed protocol are also explicitly examined with the help of the ( SCYTHER) program. In addition, the effectiveness of the suggested protocol is evaluated by determining both its excess costs and its communication costs. Therefore, it appears that the protocol is vastly superior than the many other equivalent protocols by assessing its performance and security.

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Secure Authentication and Key Management Protocol for Deployment of Internet of Vehicles (IoV) Concerning Intelligent Transport Systems

Cited by 32 publications

References 36 publications

RETRACTED ARTICLE: A vehicular network based intelligent transport system for smart cities using machine learning algorithms

RETRACTED ARTICLE: A vehicular network based intelligent transport system for smart cities using machine learning algorithms

Enhancing the Internet of Vehicles through Collaborative Cryptographic Mechanisms with IRS

A Robust Privacy Preserving Authentication Scheme for IOT Environment by 5G Technology

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