Trust-based security models in wireless sensor networks: a survey

Abdelwahab, Sarah; Gaber, Tarek; Wahed, M. El-Sayed

doi:10.1504/ijcistudies.2017.089057

Cited by 3 publications

(3 citation statements)

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“…This leaves only the second option, i.e., network-level improvements to data reconstruction, as a viable one [17], [18]. The use of trust and reputation is of particular interest in wireless sensor networks [19], mobile networks in general [20], vehicular mobile networks [21], and flying ad-hoc networks [22], to name only a few areas of application.…”

Section: Literature Reviewmentioning

confidence: 99%

“…1) The use of reputation and reputation-based algorithms is popular. The review in [19] reported that 8 out of 20 schemes used some form of reputation, while the review in [20] recorded 16 schemes out of 48 as using reputation, and the review in [21] indicated that of 111 schemes, 63 used reputation. 2) There is no typical algorithm that is used to calculate reputation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…3) Reference nodes (also known as super-nodes, observers, or agents) are the most popular solution. The reviews in [19], and [20] report the use of reference nodes in 70% and 35% of schemes, respectively. In another review of reputation-based schemes [32], 12 out of 18 schemes were found to use reference nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

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Impact of Reference Nodes on Uncertainty in Hybrid Ad-Hoc Sensor Networks

Cofta,

Marciniak

2023

IEEE Sensors J.

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The uncertainty introduced by the use of low-cost sensors (LCSs) in ad-hoc sensor networks is an ongoing concern that can be alleviated at the network level through a hybrid solution that relies on the use of reference nodes and reputation-based trust management. As reference nodes impose a significant expense, it is important to minimize their number while maximizing their impact on the reduction of uncertainty. This article presents a multidimensional analytical model developed through simulations that helps in predicting the extent of the decrease in uncertainty caused by an increase in the fraction of reference nodes in hybrid ad-hoc networks. The model shows that the marginal benefit of introducing reference nodes is much higher for networks with small fractions of such nodes, and quickly reaches near-saturation at about 5% of reference nodes, across all aspects of uncertainty.

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