Effective methods for secure data deliver in IoT
Date
2023
Authors
Editors
Advisors
Alnaghes, Mnar Saeed M
Journal Title
Journal ISSN
Volume Title
Type:
Thesis
Citation
Statement of Responsibility
Conference Name
Abstract
Internet of Things networks (IoT) have become very popular recently due to their many features that contribute to different aspects of our lives, such as health and transportation. IoT consists of multiple objects, such as sensors, tags, actuators, and mobile devices, that can communicate and collaborate without human interaction. These devices carry small memory and low-energy batteries, which affects their performance and leads to many issues. In this work, we propose and implement novel approaches for secure and efficient routing in IoT to reduce security and privacy issues of data delivery in IoT and, as a consequence, improve network performance. We divide the research into three sections, concentrating respectively on the problem of security, reliability, efficiency, and privacy in IoT data delivery. By investigating the security issues in the first part of this study, we initially identify the gaps and then introduce a novel stochastic model to characterize legitimate IoT data and malicious data in IoT-based systems. After evaluating the reliability and efficiency issues, we introduce a novel efficient approach for secure end-to-end IoT data delivery that avoids going through unreliable components and delivers data as soon as possible. To conclude the research, we study IoT data delivery privacy-preserving issues. In this part of the study, we propose a novel privacy-preserving scheme for IoT data by applying a Blockchain-based technique. We have completed four papers presenting these results, where four papers have been published. The outcomes of this study are a reference design and its practical implementation to support efficiency and security in IoT data delivery.
School/Discipline
School of Computer and Mathematical
Dissertation Note
Thesis (Ph.D.) -- University of Adelaide, School of Computer and Mathematical Sciences, 2023
Provenance
This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legals