Internet-of-Things and Information Fusion: Trust Perspective Survey

Azzedin, Farag; Ghaleb, Mustafa

doi:10.3390/s19081929

Cited by 60 publications

(30 citation statements)

References 76 publications

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“…For example, Ref. [6] lists 13 algorithms, [10] describes 26 of them, while [24] no less than 80 algorithms, strongly postulating that only data from trustworthy nodes should be processed.…”

Section: State-of-the-art-the Problem Of Measurement Uncertainty In Imentioning

confidence: 99%

Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks

Cofta

Orłowski

Lebiedź

2020

Sensors

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The aim of this paper is to introduce a NUT model (NUT: network-uncertainty-trust) that aids the decrease of the uncertainty of measurements in autonomous hybrid Internet of Things sensor networks. The problem of uncertainty in such networks is a consequence of various operating conditions and varied quality of measurement nodes, making statistical approach less successful. This paper presents a model for decreasing the uncertainty through the use of socially inspired metaphors of reputation, trust, and confidence that are the untapped latent information. The model described in the paper shows how the individual reputation of each node can be assessed on the basis of opinions provided by other nodes of the hybrid measurement network, and that this method allows to assess the extent of uncertainty the node introduces to the network. This, in turn, allows nodes of low uncertainty to have a greater impact on the reconstruction of values. The verification of the model, as well as examples of its applicability to air quality measurements are presented as well. Simulations demonstrate that the use of the model can decrease the uncertainty by up to 55% while using the EWMA (exponentially weighted moving average) algorithm, as compared to the reference one.

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Section: State-of-the-art-the Problem Of Measurement Uncertainty In Imentioning

confidence: 99%

Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks

Cofta

Orłowski

Lebiedź

2020

Sensors

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“…Data trustworthiness needs to ensure data veracity, according to the IoT system context [52] [53]. For example, supposing the IoT system collects data from tropical weather.…”

Section: B Data Trustworthinessmentioning

confidence: 99%

A Survey on Trustworthiness for the Internet of Things

Ribeiro

Kamienski

2021

IEEE Access

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IoT systems use sensors to collect data from smart environments and manage resources through data analysis. An IoT system deals with many connected devices with different network and hardware constraints in a real-world scenario. An IoT system needs to handle low-latency data analysis, security threats, internal vulnerabilities, and network disconnections, which cause data loss and incorrect decisions. Trustworthiness (also known as dependability) provides various features for an IoT end-to-end data flow, such as resilience, security, availability, reliability, scalability, maintainability, heterogeneity, hardware resources management, fault management policies, and data quality. This paper presents a survey on trustworthiness and dependability in IoT systems and proposes the Trustworthiness for IoT Framework (TW-IoT) to provide trustworthiness at the data level for mist and fog-based IoT systems. The TW-IoT framework provides data trustworthiness to ensure a continuous and uninterrupted operation of IoT data flow. We also discuss challenges and trade-offs related to data trustworthiness in IoT.

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“…However, none of them has addressed the trust management for WBAN. Furthermore, numerous surveys exist about the trust management in WSN ([ 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 ]). The application domain of these surveys considers the Mobile Adhoc Networks (MANETS), IoT (Internet of Things) or WSN.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Trust Management for WBAN: Investigations and Future Directions

Ayed

Fourati

Fares

2020

Sensors

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The rapid uptake of the Wireless Body Area Networks (WBAN) and their services poses unprecedented security requirements. WBAN are evolving to support these requirements. Fulfilling these tasks is challenging as their mobile context is increasingly complex, heterogeneous, and evolving. One potential solution to meet the WBAN security requirements is trust management that helps to reach a more secure and adaptable WBAN environment. Accordingly, this article aims to serve as a brief survey of trust management approaches within intra-WBAN and inter-WBAN. For that, we first summarize trust management concepts, discuss WBAN challenges and classify the attacks on WBAN trust management models. Subsequently, we detail and compare the existing trust based approaches in a WBAN context. We pinpoint their limitations and provide a new classification of these different approaches. We also propose a set of best practices that may help the reader to build a robust and an efficient trust management framework. We complete this survey by highlighting the open future directions and perspectives for research.

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Internet-of-Things and Information Fusion: Trust Perspective Survey

Cited by 60 publications

References 76 publications

Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks

Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks

A Survey on Trustworthiness for the Internet of Things

A Survey on Trust Management for WBAN: Investigations and Future Directions

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