Fusion of Named Data Networking and Blockchain for Resilient Internet-of-Battlefield-Things
Named Data Network's (NDN) data-centric approach makes it a suitable solution in a networking scenario where there are connectivity issues as a result of the dynamism of the network. Coupling of this ability with the blockchain's well-documented immutable trustworthy-distributed ledger fea...
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Published in: | 2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) pp. 1 - 6 |
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Main Authors: | , , , |
Format: | Conference Proceeding |
Language: | English |
Published: |
IEEE
01-01-2020
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Subjects: | |
Online Access: | Get full text |
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Summary: | Named Data Network's (NDN) data-centric approach makes it a suitable solution in a networking scenario where there are connectivity issues as a result of the dynamism of the network. Coupling of this ability with the blockchain's well-documented immutable trustworthy-distributed ledger feature, the union of blockchain and NDN in an Internet-of-Battlefield-Things (IoBT) setting could prove to be the ideal alliance that would guarantee data exchanged in an IoBT environment is trusted and less susceptible to cyber-attacks and packet losses. Various blockchain technologies, however, require that each node has a ledger that stores information or transactions in a chain of blocks. This poses an issue as nodes in an IoBT setting have varying computing and storage resources. Moreover, most of the nodes in the IoT/IoBT network are plagued with limited resources. As such, there needs to be an approach that ensures that the limited resources of these nodes are efficiently utilized. In this paper, we investigate an approach that merges blockchain and NDN to efficiently utilize the resources of these resource-constrained nodes by only storing relevant information on each node's ledger. Furthermore, we propose a sharding technique called an Interest Group and introduce a novel consensus mechanism called Proof of Common Interest. Performance of the proposed approach is evaluated using numerical results. |
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ISSN: | 2331-9860 |
DOI: | 10.1109/CCNC46108.2020.9045395 |