Description
The Internet-of-Things (IoT) paradigm is reshaping the ways to interact with the physical space. Many emerging IoT applications need to acquire, process, gain insights from, and act upon the massive amount of data continuously produced by ubiquitous IoT sensors. It is nevertheless technically challenging and economically prohibitive for each IoT application to deploy and maintain a dedicated large-scale sensor network over distributed wide geographic areas. Built upon the Sensing-as-a-Service paradigm, cloud-sensing service providers are emerging to provide heterogeneous sensing data to various IoT applications with a shared sensing substrate. Cyber threats are among the biggest obstacles against the faster development of cloud-sensing services. This dissertation presents novel solutions to achieve trustworthy IoT sensing-as-a-service. Chapter 1 introduces the cloud-sensing system architecture and the outline of this dissertation. Chapter 2 presents MagAuth, a secure and usable two-factor authentication scheme that explores commercial off-the-shelf wrist wearables with magnetic strap bands to enhance the security and usability of password-based authentication for touchscreen IoT devices. Chapter 3 presents SmartMagnet, a novel scheme that combines smartphones and cheap magnets to achieve proximity-based access control for IoT devices. Chapter 4 proposes SpecKriging, a new spatial-interpolation technique based on graphic neural networks for secure cooperative spectrum sensing which is an important application of cloud-sensing systems. Chapter 5 proposes a trustworthy multi-transmitter localization scheme based on SpecKriging. Chapter 6 discusses the future work.
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Details
Title
- Trustworthy IoT Sensing-as-a-Service
Contributors
- Zhang, Yan (Author)
- Zhang, Yanchao YZ (Thesis advisor)
- Fan, Deliang (Committee member)
- Xue, Guoliang (Committee member)
- Reisslein, Martin (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2022
Subjects
Resource Type
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Note
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Partial requirement for: Ph.D., Arizona State University, 2022
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Field of study: Computer Engineering