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Trustworthy IoT Sensing-as-a-Service.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Trustworthy IoT Sensing-as-a-Service./
Author:	Zhang, Yan.
Description:	1 online resource (165 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-02, Section: B.
Contained By:	Dissertations Abstracts International84-02B.
Subject:	Computer engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798841777311

Trustworthy IoT Sensing-as-a-Service.
Zhang, Yan.

Trustworthy IoT Sensing-as-a-Service. - 1 online resource (165 pages)

Source: Dissertations Abstracts International, Volume: 84-02, Section: B.

Thesis (Ph.D.)--Arizona State University, 2022.

Includes bibliographical references

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.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798841777311Subjects--Topical Terms:

569006
Computer engineering.
Subjects--Index Terms:

Internet of thingsIndex Terms--Genre/Form:

554714
Electronic books.

Trustworthy IoT Sensing-as-a-Service.
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520 $a 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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