This book, at first, explores the evolution of the Io T to SIo T and offers a comprehensive understanding of SIo T and trust management vis-à-vis SIo T. It subsequently envisages trust quantification models by employing key SIo T-specific trust features, including SIo T relationships (e.g., friendships, working relationships, and community-of-interest), direct observations, and indirect observations, to augment the idea of trust quantification of a SIo T 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 SIo T.
Зміст
Introduction.- Understanding the Trustworthiness Management in the SIo T Network.- Towards Trust Quantification in the SIo T Network.- A Machine Learning based Trust Computational Heuristic for the SIo T Network.- Towards Trustworthy Object Classification in the SIo T Network.- Summary and Future Directions of the Book.
Про автора
Subhash Sagar holds a Ph.D. from Macquarie University, Sydney, Australia. He has shared his expertise as Associate Research Fellow at Deakin University and as Lecturer at the Victorian Institute of Technology. Previously, Subhash served as Faculty Member at the Department of Computer Science, National University of Computer and Emerging Sciences, Karachi, Pakistan. His research interests encompass the Internet of Things, Social Internet of Things, and Trust Management, evident in his numerous publications in prestigious journals and conferences. With around 20 publications in reputable conferences such as ICC, GLOBCOM, and Sen Sys and journals including IEEE Transactions on Network and Service Management, ACM Transactions on Cyber-Physical Systems, and Springer Computing, Subhash actively contributes to academia. He engages as Reviewer for esteemed publications like IEEE Networking Letters, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Vehicular Technology, and MDPI Sensors and serves as Technical Program Committee Member and Reviewer for notable conferences.
Adnan Mahmood possesses a Ph.D. in Computer Science and is Lecturer in Computing—Io T and Networking at the School of Computing, Macquarie University, Sydney, Australia. Before moving to Macquarie University, Adnan has spent a considerable number of years in both academic and research settings of the Republic of Ireland, Malaysia, Pakistan, and the People’s Republic of China. His research interests include, but are not limited to, the Internet of Things (primarily, the Internet of Vehicles), Trust Management, Software-Defined Networking, and the Next Generation Heterogeneous Wireless Networks. Adnan has 70+ publications as refereed book chapters, journal articles, and conference papers with a number of them published in prestigious venues, including but not limited to, ACM Computing Surveys, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Network and Service Management, ACM Transactions on Sensor Networks, ACM Transactions on Cyber-Physical Systems, and Nature’s Scientific Reports. Adnan, besides, serves on the Technical Program Committees of a number of reputed international conferences. He is Member of the IEEE, IET, and the ACM.
Quan Z. Sheng is Distinguished Professor and Head of School of Computing at Macquarie University, Australia. Before moving to Macquarie University, Michael spent 10 years at School of Computer Science, the University of Adelaide, serving in a number of senior leadership roles including interim Head and Deputy Head of School of Computer Science. Michael holds a Ph.D. degree in computer science from the University of New South Wales (UNSW) and did his post-doc as Research Scientist at CSIRO ICT Centre. From 1999 to 2001, Michael worked at UNSW as Visiting Research Fellow. Prior to that, he spent six years as Senior Software Engineer in industries. Prof. Sheng is ranked by Microsoft Academic as one of the Most Impactful Authors in Services Computing (ranked Top 5 of All Time worldwide) and in the Web of Things (ranked Top 20 All Time). He is the recipient of the AMiner Most Influential Scholar Award on Io T (2007-2017), ARC (Australian Research Council) Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003). Prof Michael Sheng is Vice Chair of the Executive Committee of the IEEE Technical Community on Services Computing (IEEE TCSVC) and Member of the ACS (Australian Computing Society) Technical Advisory Board on Io T.
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