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The Effects of Inadequate Cybersecur...

Abdullah, Baqui.

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The Effects of Inadequate Cybersecurity Controls on Data Integrity in Wearable IoT Devices.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The Effects of Inadequate Cybersecurity Controls on Data Integrity in Wearable IoT Devices./
Author:	Abdullah, Baqui.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2024,
Description:	212 p.
Notes:	Source: Dissertations Abstracts International, Volume: 85-11, Section: A.
Contained By:	Dissertations Abstracts International85-11A.
Subject:	Information technology. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31240251
ISBN:	9798382720388

The Effects of Inadequate Cybersecurity Controls on Data Integrity in Wearable IoT Devices.
Abdullah, Baqui.

The Effects of Inadequate Cybersecurity Controls on Data Integrity in Wearable IoT Devices. - Ann Arbor : ProQuest Dissertations & Theses, 2024 - 212 p.

Source: Dissertations Abstracts International, Volume: 85-11, Section: A.

Thesis (Ph.D.)--University of the Cumberlands, 2024.

The noticeable growth of the Internet of Things extends the phenomenal global Internet that facilitates connections and collecting data without human intervention. The problem is that inadequate cybersecurity controls in wearable devices reduce data integrity. The purpose of this study was to investigate inadequate cybersecurity controls to provide insight for leadership into how to eliminate or reduce data integrity concerns users may have with wearable devices that collect data from users, creating security issues for the user of wearable devices. The research questions examined the correlation between key independent variables: perceived risk, performance expectancy, effort expectancy, trust, self-efficacy, perceived enjoyment, satisfaction, and dependent variable behavioral intentions. Partial Least Squares-Structural Equation Modeling was the statistical tool for investigating the extended Unified Theory of Acceptance and Use of Technology model. These eight variables in the model represented the embodiment of eight latent variables examined through 31 observed variables. This investigation's findings indicated a significant correlation between the independent variable and the effect on an individual's willingness to wear wearable devices. Performance expectancy, effort expectancy, and satisfaction had the most influential statistical relationship on behavioral intentions. The findings suggest that individuals' risk perceptions significantly affect their intentions to engage with wearables. The lack of transparency of existing risks in wearables generates unwarranted trust from end-users to acquire wearables. A future recommendation is to use an artificial neural network to ascertain the predictive strength of the variables in the model.

ISBN: 9798382720388Subjects--Topical Terms:

532993
Information technology.
Subjects--Index Terms:

Cybersecurity

The Effects of Inadequate Cybersecurity Controls on Data Integrity in Wearable IoT Devices.
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500 $a Advisor: Dey, Sukhen.
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520 $a The noticeable growth of the Internet of Things extends the phenomenal global Internet that facilitates connections and collecting data without human intervention. The problem is that inadequate cybersecurity controls in wearable devices reduce data integrity. The purpose of this study was to investigate inadequate cybersecurity controls to provide insight for leadership into how to eliminate or reduce data integrity concerns users may have with wearable devices that collect data from users, creating security issues for the user of wearable devices. The research questions examined the correlation between key independent variables: perceived risk, performance expectancy, effort expectancy, trust, self-efficacy, perceived enjoyment, satisfaction, and dependent variable behavioral intentions. Partial Least Squares-Structural Equation Modeling was the statistical tool for investigating the extended Unified Theory of Acceptance and Use of Technology model. These eight variables in the model represented the embodiment of eight latent variables examined through 31 observed variables. This investigation's findings indicated a significant correlation between the independent variable and the effect on an individual's willingness to wear wearable devices. Performance expectancy, effort expectancy, and satisfaction had the most influential statistical relationship on behavioral intentions. The findings suggest that individuals' risk perceptions significantly affect their intentions to engage with wearables. The lack of transparency of existing risks in wearables generates unwarranted trust from end-users to acquire wearables. A future recommendation is to use an artificial neural network to ascertain the predictive strength of the variables in the model.
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