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    VABLOCK: a blockchain-based secure communication in V2V network using ICN network support technology

    Ali, A, Iqbal, MM, Jabbar, S, Asghar, MN, Raza, U and Al-Turjman, F (2022) VABLOCK: a blockchain-based secure communication in V2V network using ICN network support technology. Microprocessors and Microsystems, 93. p. 104569. ISSN 0141-9331

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    Abstract

    Vehicular Ad hoc Network (VANET) provides efficient communication among vehicles (V2V). The communication among all the vehicles complies with the on-demand, which contains a secure and trustable mechanism to ensure trustable communication. The modification in the communication information may result in falsified information. Secure data is very important in V2V communication to save the lives of pedestrians and drives by delivering secure and accurate information. To address the problem and achieve secure communication in V2V, we proposed a new blockchain-based message dissemination technique to secure V2V communication. With the passive need for adaptable and sufficient content delivery, information-centric networking (ICN) is adopted to enhance trustworthiness communication in VANET. We used Cluster-based secure communication through ICN-based VANETs. As VANET is open, ICN provides direct content requests and responses without location dependency. ICN-based VANET enhances caching abilities. The blockchain-based security protocol is implemented to secure efficient communication without altering the messages. The protocol achieves privacy, security, and trust for detecting malicious nodes in VANET. Additionally, the Clustering technique is applied to adopt in-range communication. Proposed-Caching framework enhances security and provides on-demand data to vehicles. NS-2 simulator is used to simulate the Proposed VABLOCK approach. Experimental results are performed and compared with relevant techniques, which show enhanced results based on cache hit ratio, one hop count, malicious node detection, and delivery ratio. We demonstrate that proposed caching improves results on selected parameters based on results.

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