Towards Resilient Social IoT Sensors and Networks [electronic resource] : A Trust Management Approach / by Subhash Sagar, Adnan Mahmood, Quan Z. Sheng.

Por: Sagar, Subhash [author.]Colaborador(es): Mahmood, Adnan [author.] | Sheng, Quan Z [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Smart Sensors, Measurement and Instrumentation ; 48Editor: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XIV, 114 p. 38 illus., 37 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031607011Tema(s): Internet of things | Materials | Detectors | Machine learning | Internet of Things | Sensors and biosensors | Machine LearningFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 004.678 Clasificación LoC:TK5105.8857Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Understanding the Trustworthiness Management in the SIoT Network -- Towards Trust Quantification in the SIoT Network -- A Machine Learning based Trust Computational Heuristic for the SIoT Network -- Towards Trustworthy Object Classification in the SIoT Network -- Summary and Future Directions of the Book.
En: Springer Nature eBookResumen: This book, at first, explores the evolution of the IoT to SIoT and offers a comprehensive understanding of SIoT and trust management vis-à-vis SIoT. It subsequently envisages trust quantification models by employing key SIoT-specific trust features, including SIoT relationships (e.g., friendships, working relationships, and community-of-interest), direct observations, and indirect observations, to augment the idea of trust quantification of a SIoT object. Furthermore, diverse trust aggregation techniques, i.e., conventional weighted sum, machine learning, and artificial neural networks, are proposed so as to address the challenges of the trust aggregation. Finally, the book outlines the future research directions for emphasizing the importance of trustworthiness management in the evolving notion of the SIoT.
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Introduction -- Understanding the Trustworthiness Management in the SIoT Network -- Towards Trust Quantification in the SIoT Network -- A Machine Learning based Trust Computational Heuristic for the SIoT Network -- Towards Trustworthy Object Classification in the SIoT Network -- Summary and Future Directions of the Book.

This book, at first, explores the evolution of the IoT to SIoT and offers a comprehensive understanding of SIoT and trust management vis-à-vis SIoT. It subsequently envisages trust quantification models by employing key SIoT-specific trust features, including SIoT relationships (e.g., friendships, working relationships, and community-of-interest), direct observations, and indirect observations, to augment the idea of trust quantification of a SIoT object. Furthermore, diverse trust aggregation techniques, i.e., conventional weighted sum, machine learning, and artificial neural networks, are proposed so as to address the challenges of the trust aggregation. Finally, the book outlines the future research directions for emphasizing the importance of trustworthiness management in the evolving notion of the SIoT.

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