2020
DOI: 10.1145/3408292
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A Survey on Trust Evaluation Based on Machine Learning

Abstract: Trust evaluation is the process of quantifying trust with attributes that influence trust. It faces a number of severe issues such as lack of essential evaluation data, demand of big data process, request of simple trust relationship expression, and expectation of automation. In order to overcome these problems and intelligently and automatically evaluate trust, machine learning has been applied into trust evaluation. Researchers have proposed many methods to use machine learning for trust evaluation. However,… Show more

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Cited by 73 publications
(65 citation statements)
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“…With the concepts of edge computing and fog computing [37], a layered architecture is formed for the IoT. As shown in Figure 1, the architecture is composed of 3 layers: the device layer, the edge and fog layer, and the cloud layer.…”
Section: Learning-based Trust Computational Methods a System Modelmentioning
confidence: 99%
“…With the concepts of edge computing and fog computing [37], a layered architecture is formed for the IoT. As shown in Figure 1, the architecture is composed of 3 layers: the device layer, the edge and fog layer, and the cloud layer.…”
Section: Learning-based Trust Computational Methods a System Modelmentioning
confidence: 99%
“…Privacy A secure trust model preserves privacy [1], [6], [9]. This means it allows users to select the type, method and to whom their personal information can be accessed.…”
Section: A Securitymentioning
confidence: 99%
“…"Distrust" implies that the user is repelled by the node whereas "no trust" or "neutral" could simply be that there is insufficient information or conflicting information respectively about the user's trustworthiness. Context Aware Since trust is by nature a highly situational concept, trust models need to consider the different situations and how they affect trust [6], [9]. Not only do they have to consider the different situations, they have to do so appropriately, choosing suitable contextual features that inform a node's trust the most.…”
Section: B Comprehensivenessmentioning
confidence: 99%
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