Secure V2V Communication with Identity-based Cryptography from License Plate Recognition

Andreica, Tudor; Groza, Bogdan

doi:10.1109/iotsms48152.2019.8939216

Cited by 6 publications

(7 citation statements)

References 24 publications

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“…On the other hand, it is important to notice that there are works on the literature dealing with vehicle plate identification using technologies not listed above. For instance, Andreica and Groza [42] experiment the use of the license to identify vehicles and use this identification number to bootstrap security based on identity-based cryptography schemes. In this sense, their performed experiments with Android smartphones in order to determine the feasibility of the solution.…”

Section: Related Workmentioning

confidence: 99%

Performance and Security Evaluation on a Blockchain Architecture for License Plate Recognition Systems

et al. 2021

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Since the early 2000s, life in cities has changed significantly due to the Internet of Things (IoT). This concept enables developers to integrate different devices collecting, storing, and processing a large amount of data, enabling new services to improve various professional and personal activities. However, privacy issues arise with a large amount of data generated, and solutions based on blockchain technology and smart contract have been developed to address these issues. Nevertheless, several issues must still be taken into account when developing blockchain architectures aimed at the IoT scenario because security flaws still exist in smart contracts, mainly due to the lack of ease when building the code. This article presents a blockchain storage architecture focused on license plate recognition (LPR) systems for smart cities focusing on privacy, performance, and security. The proposed architecture relies on the Ethereum platform. Each smart contract matches the privacy preferences of a license plate to be anonymized through public encryption. The storage of data captured by the LPR system can only be done if the smart contract enables it. However, in the case of motivation foreseen by the legislation, a competent user can change the smart contract and enable the storage of the data captured by the LPR system. Experimental results show that the performance of the proposed architecture is satisfactory, regarding the scalability of the built private network. Furthermore, tests on our smart contract using security and structure analysis tools on the developed script demonstrate that our solution is fraud-proof. The results obtained in all experiments bring evidence that our architecture is feasible to be used in real scenarios.

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Section: Related Workmentioning

confidence: 99%

Performance and Security Evaluation on a Blockchain Architecture for License Plate Recognition Systems

et al. 2021

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“…El uso de criptografía basada en identidades para la comunicación intervehicular ha sido considerado previamente [19], [20], así como en el contexto de las VANETS (Vehicle Adhoc Networks) [19] se han propuesto esquemas donde la autenticación se basa en pseudónimos (identificadores aleatorios) [21] o se utilizan esquemas de firma de grupo [22].…”

Section: Ii-b Comunicaciones V2v Seguras Usando Criptografía Basada E...unclassified

“…La mayoría de estas propuestas no especifican qué información usar como identidad. En [20] se propone utilizar como identidades las matrículas de los coches, previamente reconocidas a través de cámaras de teléfonos inteligentes disponibles en los vehículos. Sin embargo, la cadena de caracteres que suele usarse en la identificación de vehículos es el número de bastidor dado que es único, a diferencia de la matricula, que puede variar por cambio de país o por propia re-matriculación del vehículo.…”

Section: Ii-b Comunicaciones V2v Seguras Usando Criptografía Basada E...unclassified

Protocolo de comunicación entre vehículos basado en el número de bastidor digital

Escapa¹,

Corona²

2021

Colección Jornadas Y Congresos

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“…However, public groups and average citizens have questioned whether they maintain private information tied to recognized license plates. Due to the numerous time entries in the ALPR database and its restricted access, which poses a serious privacy risk, law enforcement agencies have dramatically boosted their use of ALPR devices [13,14]. Additionally, the ALPR approach may mistakenly identify similar objects like billboards and traffic signs as license plates [15].…”

Section: Introductionmentioning

confidence: 99%

YOLO and Blockchain Technology Applied to Intelligent Transportation License Plate Character Recognition for Security

Alharbi,

Alshahrani,

Zakariah

et al. 2023

CMC

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Privacy and trust are significant issues in intelligent transportation systems (ITS). Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels, optical fiber, and blockchain technology. The Internet of Things (IoT) is a network of connected, interconnected gadgets. Privacy issues occasionally arise due to the amount of data generated. However, they have been primarily addressed by blockchain and smart contract technology. While there are still security issues with smart contracts, primarily due to the complexity of writing the code, there are still many challenges to consider when designing blockchain designs for the IoT environment. This study uses traditional blockchain technology with the "You Only Look Once" (YOLO) object detection method to accurately locate and identify license plates. While YOLO and blockchain technologies used for intelligent vehicle license plate recognition are promising, they have received limited research attention. Real-time object identification and recognition would be possible by combining a cutting-edge object detection technique with a regional convolutional neural network (RCNN) built with the tensor flow core open source libraries. This method works reasonably well for identifying any license plate. The Automatic License Plate Recognition (ALPR) approach delivered outstanding results in various datasets. First, with a recognition rate of 96.2%, our system (UFPR-ALPR) surpassed the previously used technology, consisting of 4500 frames and around 150 films. Second, a deep learning algorithm was trained to recognize images of license plate numbers using the UFPR-ALPR dataset. Third, the license plate's characters were complicated for standard methods to identify because of the shifting lighting correctly. The proposed model, however, produced beneficial outcomes. KEYWORDS Intelligent transportation system; blockchain technology; license plate recognition; privacy; YOLO; deep learning technique; ALPRAdditionally, noise removal techniques such as Gaussian blur and median filtering were applied to remove any noise or artifacts in the license plate images. Finally, the pre-processed dataset was split into training, and testing sets with a ratio of 80:20 to evaluate the model's performance on unseen data. These pre-processing techniques ensure that the license plate recognition model is trained on a high-quality dataset, leading to improved accuracy in the recognition process. Materials and MethodsInformation about traffic management, environmental changes, and congestion is gathered and disseminated through a transportation system known as ITS. Communications between vehicles and between vehicles and infrastructure are made possible by ITS in various ways. In addition, ITS includes information from both wired and wireless connections. Infrastructure-to-infrastructure communication typically uses cable technology, while V2V and V2I communication frequently use wireles...

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Secure V2V Communication with Identity-based Cryptography from License Plate Recognition

Cited by 6 publications

References 24 publications

Performance and Security Evaluation on a Blockchain Architecture for License Plate Recognition Systems

Performance and Security Evaluation on a Blockchain Architecture for License Plate Recognition Systems

Protocolo de comunicación entre vehículos basado en el número de bastidor digital

YOLO and Blockchain Technology Applied to Intelligent Transportation License Plate Character Recognition for Security

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