Error reconciliation with turbo codes for secret key generation in vehicular ad hoc networks
Abstract
© Springer Nature Switzerland AG 2019. We present an algorithm that allows two users to establish a symmetric cryptographic key by incorporating the most important features of the wireless channel in vehicle-to-vehicle (V2V) communication. The proposed model includes surrounding scatterers’ mobility by considering other vehicles; it also includes three-dimensional (3D) multipath propagation. These temporal variability attributes are incorporated into the key generation process where non-reciprocity compensation is combined with turbo codes (TCs). For fair comparisons, the indexing technique is applied in conjunction with the non-reciprocity compensation technique. A series of simulations are run to calculate key performance indicators (KPIs). The entropy values were high throughout all rounds of simulation and estimated around 0.94 to 0.99 bits per sample. Furthermore, simulation results reveal a decrease in bit mismatch rate (BMR) and an increase key generation rate (KGR) when TCs are used. The estimated BMR is nearly the same for different key lengths, and it is estimated to only 0.02 with TCs, compared to 0.22 obtained with the indexing technique. Finally, the key generation rate was also reported high ranging from 35 to 39 for the 128-bit symmetric keys per minute with TCs, while it is ranging from 3 to 7 when compared with a sample indexing technique published in the public domain.Citation
Kbaier Ben Ismail, D., Karadimas, P., Epiphaniou, G. and Al-Khateeb, H. M. (2018) Error reconciliation with turbo codes for secret key generation in vehicular ad hoc networks, in Arai, K., Kapoor, S. and Bhatia, R. (eds.) Intelligent Computing: Proceedings of the 2018 Computing Conference, Volume 2. Switzerland: Springer, pp. 696-704.Publisher
Springer International PublishingAdditional Links
https://link.springer.com/chapter/10.1007%2F978-3-030-01177-2_51Type
Conference contributionLanguage
enDescription
Paper originally delivered at the Science and Information Conference 2018.Series/Report no.
Advances in Intelligent Systems and Computing, 857ISSN
2194-5357EISSN
2194-5365ae974a485f413a2113503eed53cd6c53
10.1007/978-3-030-01177-2_51
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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/