Vehicular networks with security and trust management solutions: proposed secured message exchange via blockchain technology

• Published in: Wireless networks Vol. 26; no. 6; pp. 4207 - 4226
• Main Authors: Malik, Nisha, Nanda, Priyadarsi, He, Xiangjian, Liu, Ren Ping
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2020; Springer Nature B.V
• Subjects: Algorithms; Authentication; Blockchain; Communication; Communications Engineering; Computer Communication Networks; Cryptography; Electrical Engineering; Engineering; IT in Business; Machine learning; Management; Measurement methods; Message passing; Mobile ad hoc networks; Networks; Nodes; Optimization; Optimization algorithms; Trust; Trustworthiness; Vehicles; Wireless networks; VANET; Trust evaluation; Key generation; Data sanitization; Optimization
• ISSN: 1022-0038; 1572-8196
• DOI: 10.1007/s11276-020-02325-z

In vehicular ad hoc networks (VANET), effective trust establishment with authentication is an important requirement. Trust management among communicating vehicles is significant for secure message transmission; however, very less contributions have been made towards evaluating the trustworthiness of the node. This research work intends to introduce a new trust management system in VANET with two major phases: secured message transmission and node trustability prediction. The security assured message passing is carried out by incorporating the privacy preservation model under the data sanitization process. The key used for the sanitization process is optimally tuned by a new hybrid algorithm termed Sea Lion Explored-Whale Optimization Algorithm, which is the combination of Whale Optimization Algorithm and Sea Lion Optimization Algorithm, respectively. The blockchain technology is assisted to handle the key generated by the nodes. Subsequently, the trustability of the node is evaluated under novel specifics “two-level evaluation process” with a rule-based and machine learning-based evaluation process. Finally, the performance of the proposed model is verified and proved over other conventional methods for certain measures.