2022
DOI: 10.1007/s00607-021-01040-7
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Trust on wheels: Towards secure and resource efficient IoV networks

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Cited by 22 publications
(11 citation statements)
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“…The computation starts with the coefficient c 2 t −1 and proceeds in reverse order until the first coefficient c i = 0 is reached. In that case, the index imax = i and, consequently, the parameter LC are computed via Equation (5). Algorithm 1 illustrates this computation.…”
Section: Computation Of Lc By Means Of the B-representationmentioning
confidence: 99%
See 2 more Smart Citations
“…The computation starts with the coefficient c 2 t −1 and proceeds in reverse order until the first coefficient c i = 0 is reached. In that case, the index imax = i and, consequently, the parameter LC are computed via Equation (5). Algorithm 1 illustrates this computation.…”
Section: Computation Of Lc By Means Of the B-representationmentioning
confidence: 99%
“…The security of an IoT network involves different techniques, i.e., blockchain, trust management [3][4][5], as well as cryptographic mechanisms. Cryptographic security is needed to prevent users from losing data and to avoid risks related to the inappropriate use of passwords.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…As this approach improves reliability, it can also be used to improve GPS positioning accuracy by using data between objects, such as self-driving cars [18,39]. However, there are cases where the blockchain is not suitable for rapid communication in an environment, such as internet of vehicles, because it consumes relatively high energy compared to the cryptography technique [40,41]. In addition, it is limited in that it has the same weakness as the 51% attack, in that it trusts all nodes without evaluating the reputation [42].…”
Section: Blockchainmentioning
confidence: 99%
“…This parameter can track the misbehavior of the trustee and view their history, so that the trustor can determine whether to have further communication with the trustee [37]. In [41,49], using joint deep learning to evaluate the degree of trust between users and task assignors, the author designed a layered incentive mechanism to realize reasonable and fair rewards and punishments, which improved the accuracy of trust evaluation.…”
mentioning
confidence: 99%