2019
DOI: 10.1109/access.2019.2902843
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Selective Authentication Based Geographic Opportunistic Routing in Wireless Sensor Networks for Internet of Things Against DoS Attacks

Abstract: Wireless Sensor Networks (WSNs) have been widely used as the communication system in the Internet of Things (IoT). In addition to the services provided by WSNs, many IoT-based applications require reliable data delivery over unstable wireless links. To guarantee reliable data delivery, existing works exploit geographic opportunistic routing with multiple candidate forwarders in WSNs. However, these approaches suffer from serious Denial of Service (DoS) attacks, where a large number of invalid data are delibera… Show more

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Cited by 57 publications
(27 citation statements)
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“…• Routing Metric (RM) [80]: In the context of WSNs for IoT, this metric, which apparently does not offer any specific novelty, linearly combines the one-hop geographical progress times the one-hop link trust, and the residual energy of the next-hop node as follows:…”
Section: • Multicast Expected Advancement Rate (Mear) I-mearmentioning
confidence: 99%
“…• Routing Metric (RM) [80]: In the context of WSNs for IoT, this metric, which apparently does not offer any specific novelty, linearly combines the one-hop geographical progress times the one-hop link trust, and the residual energy of the next-hop node as follows:…”
Section: • Multicast Expected Advancement Rate (Mear) I-mearmentioning
confidence: 99%
“…Because of the popularity of WSN, it is also researched in terms of networking method [23], network coverage [24], information security [25], [26], privacy protection [27], source localization [28] and fog computing [29].…”
Section: Related Workmentioning
confidence: 99%
“…Selective authentication based geographic opportunistic routing is proposed by Lyu et al 12 for preventing denial of service attacks in WSN routing for IoT. This routing is based on the trust constructed using statistic state information of the communicating links.…”
Section: Related Workmentioning
confidence: 99%