A patient agent controlled customized blockchain based framework for internet of things
- Authors: Uddin, Md Ashraf
- Date: 2021
- Type: Text , Thesis , PhD
- Full Text:
- Description: Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.
- Description: Doctor of Philosophy
- Authors: Uddin, Md Ashraf
- Date: 2021
- Type: Text , Thesis , PhD
- Full Text:
- Description: Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.
- Description: Doctor of Philosophy
Factors affecting the organisational adoption of blockchain technology in australia : a mixed-methods approach
- Authors: Malik, Muhammad Saleem
- Date: 2022
- Type: Text , Thesis , PhD
- Full Text:
- Description: Blockchain (BCT) is an emerging technology that promises many benefits for organisations, such as disintermediation, data security, data transparency, a single version of the truth, and trust among trading partners. Despite its multiple benefits, the adoption rate of BCT among organisations has not reached a significantly high level worldwide. The present thesis addresses this issue in the Australian context. There is a knowledge gap in what specific factors, among the plethora of factors reported in the extant scholarly and commercial literature, affect Australian organisations while deciding to adopt BCT. To fill this gap, this thesis uses a mixed-methods approach known as sequential exploratory mixed methods. In this approach, the research starts with a qualitative phase as an initial phase followed by a quantitative phase. During the qualitative phase, data were collected through semi-structured interviews of the BCT experts and decision-makers working with the ifferent Australian organisations that adopted or were in the process of adopting BCT. The Technology, Organisation, Environment (TOE) framework, based on the qualitative interpretative approach, was used as a theoretical lens during the qualitative phase. The qualitative data were analyzed using the thematic analysis technique with the SQR NVivo software. The analysis shows that the different factors, belonging to the technological, organisational, and environmental contexts, affect the organisational decision to adopt BCT in Australia. The technological factors include perceived benefits, perceived computability, perceived complexity, perceived disintermediation, and perceived information transparency; organisational factors are organisational innovativeness, organisational learning capability, top management support; environmental factors consist of government support, standards uncertainty, competition intensity, and trading partners readiness. The qualitative analysis also shows the direct and moderating effect of the perceived risks between the relationship of the identified factors and organisational adoption of BCT. Based on the findings of the qualitative phase, the thesis develops a theoretical conceptual model, which shows the relationship between the factors and the organisational adoption of BCT. To increase the external validity of the developed conceptual model, the thesis started a quantitative phase with the administration of an online survey for data collection. Certain criteria were set to screen out the irrelevant participants in the survey. During this phase, hypotheses were proposed for the relationship of the factors identified in the qualitative phase and the organisational adoption of BCT. The survey data was analyzed using the PLS Structural Equation Modelling (SEM) technique with the SmartPLS 3 software. The quantitative analysis confirms the findings of the qualitative phase that the perceived benefits, perceived compatibility, perceived information transparency, perceived disintermediation, organisational innovativeness, organisational learning capability, top management support, competitive intensity, government support, and trading partner readiness have a positive effect on the organisational adoption of BCT. Whereas the perceived complexity, standards uncertainty, and perceived risks have a negative effect. The analysis also shows that the moderating effects of perceived risks are significant in the relationship of perceived compatibility, perceived information transparency, perceived disintermediation, organisational innovativeness, organisation innovativeness, competition intensity, and organisational adoption of BCT. Contrary to the qualitative findings, ‘perceived risks’ has no moderating effects on the relationship of perceived benefits, organisational learning capability, top management support, government support, trading partner readiness, and the adoption of BCT. The thesis has both theoretical and practical contributions, which are useful both for theory development and decision-making for the adoption of BCT in Australia. Theoretically, this thesis contributes to the existing IT adoption literature in several ways. Firstly, the thesis provides empirical evidence about the factors affecting organisational adoption of BCT in Australia. This is the first in-depth sequential exploratory mixed methods research that bridges this knowledge gap in the extant literature. The identification of such factors is important, particularly for the Australian government and organisations interested in the value creation of BCT. Second, the thesis reports the effect of new factors, namely, perceived information transparency, perceived disintermediation, organisational innovativeness, organisational learning capability, standards uncertainty, trading partner readiness, and competition intensity on BCT adoption that are exclusively identified in this research. Third, this thesis confirms the findings of the past studies that the factors of perceived benefits and perceived compatibility, perceived complexity, and top management support have an effect on the organisational adoption of BCT. Fourth, according to the best of the authors' knowledge, this is the first research that has used the qualitative interpretive research approach to investigate the organisational adoption of BCT. Therefore, the thesis confirms the suitability of the qualitative interpretive research approach for BCT adoption. Lastly, most of the researchers have used the TOE framework in either in qualitative or quantitative research. This thesis proves its validity in mixed methods research as well. The thesis's practical contributions are discussed in chapter 7.
- Description: Doctor of Philosophy
- Authors: Malik, Muhammad Saleem
- Date: 2022
- Type: Text , Thesis , PhD
- Full Text:
- Description: Blockchain (BCT) is an emerging technology that promises many benefits for organisations, such as disintermediation, data security, data transparency, a single version of the truth, and trust among trading partners. Despite its multiple benefits, the adoption rate of BCT among organisations has not reached a significantly high level worldwide. The present thesis addresses this issue in the Australian context. There is a knowledge gap in what specific factors, among the plethora of factors reported in the extant scholarly and commercial literature, affect Australian organisations while deciding to adopt BCT. To fill this gap, this thesis uses a mixed-methods approach known as sequential exploratory mixed methods. In this approach, the research starts with a qualitative phase as an initial phase followed by a quantitative phase. During the qualitative phase, data were collected through semi-structured interviews of the BCT experts and decision-makers working with the ifferent Australian organisations that adopted or were in the process of adopting BCT. The Technology, Organisation, Environment (TOE) framework, based on the qualitative interpretative approach, was used as a theoretical lens during the qualitative phase. The qualitative data were analyzed using the thematic analysis technique with the SQR NVivo software. The analysis shows that the different factors, belonging to the technological, organisational, and environmental contexts, affect the organisational decision to adopt BCT in Australia. The technological factors include perceived benefits, perceived computability, perceived complexity, perceived disintermediation, and perceived information transparency; organisational factors are organisational innovativeness, organisational learning capability, top management support; environmental factors consist of government support, standards uncertainty, competition intensity, and trading partners readiness. The qualitative analysis also shows the direct and moderating effect of the perceived risks between the relationship of the identified factors and organisational adoption of BCT. Based on the findings of the qualitative phase, the thesis develops a theoretical conceptual model, which shows the relationship between the factors and the organisational adoption of BCT. To increase the external validity of the developed conceptual model, the thesis started a quantitative phase with the administration of an online survey for data collection. Certain criteria were set to screen out the irrelevant participants in the survey. During this phase, hypotheses were proposed for the relationship of the factors identified in the qualitative phase and the organisational adoption of BCT. The survey data was analyzed using the PLS Structural Equation Modelling (SEM) technique with the SmartPLS 3 software. The quantitative analysis confirms the findings of the qualitative phase that the perceived benefits, perceived compatibility, perceived information transparency, perceived disintermediation, organisational innovativeness, organisational learning capability, top management support, competitive intensity, government support, and trading partner readiness have a positive effect on the organisational adoption of BCT. Whereas the perceived complexity, standards uncertainty, and perceived risks have a negative effect. The analysis also shows that the moderating effects of perceived risks are significant in the relationship of perceived compatibility, perceived information transparency, perceived disintermediation, organisational innovativeness, organisation innovativeness, competition intensity, and organisational adoption of BCT. Contrary to the qualitative findings, ‘perceived risks’ has no moderating effects on the relationship of perceived benefits, organisational learning capability, top management support, government support, trading partner readiness, and the adoption of BCT. The thesis has both theoretical and practical contributions, which are useful both for theory development and decision-making for the adoption of BCT in Australia. Theoretically, this thesis contributes to the existing IT adoption literature in several ways. Firstly, the thesis provides empirical evidence about the factors affecting organisational adoption of BCT in Australia. This is the first in-depth sequential exploratory mixed methods research that bridges this knowledge gap in the extant literature. The identification of such factors is important, particularly for the Australian government and organisations interested in the value creation of BCT. Second, the thesis reports the effect of new factors, namely, perceived information transparency, perceived disintermediation, organisational innovativeness, organisational learning capability, standards uncertainty, trading partner readiness, and competition intensity on BCT adoption that are exclusively identified in this research. Third, this thesis confirms the findings of the past studies that the factors of perceived benefits and perceived compatibility, perceived complexity, and top management support have an effect on the organisational adoption of BCT. Fourth, according to the best of the authors' knowledge, this is the first research that has used the qualitative interpretive research approach to investigate the organisational adoption of BCT. Therefore, the thesis confirms the suitability of the qualitative interpretive research approach for BCT adoption. Lastly, most of the researchers have used the TOE framework in either in qualitative or quantitative research. This thesis proves its validity in mixed methods research as well. The thesis's practical contributions are discussed in chapter 7.
- Description: Doctor of Philosophy
Every crypto breath in the world : the current global position of the cryptocurrency market and future prediction
- Authors: Jayawardhana, Asanga
- Date: 2022
- Type: Text , Thesis , PhD
- Full Text:
- Description: This study was motivated by the breakthrough of cryptocurrencies in 2018. The other main reasons behind the motivation are the total market capitalisation of one trillion-dollar diversification possibilities and the lack of preceding scientific research to identify the portfolio diversification possibilities of cryptocurrencies from many angles. Four empirical studies were conducted to provide a holistic view of cryptocurrency as an investment tool. The first study investigated the portfolio diversification possibilities between cryptocurrencies and traditional financial markets. A quantitative method was employed with Cointegration, ARDL bound testing approach, causality, and co-movement testing. Applying Modern portfolio theory to identify the diversification possibilities between the aforementioned markets enabled the study to highlight how investors can reap the benefits of cryptocurrencies. The second study extended the investigation of the portfolio diversification possibilities of cryptocurrency by including precious metals and cryptocurrencies in the same investment basket. Investors switch from traditional investment assets, such as equity and debt market instruments, to precious metal markets to reap benefits. Therefore, this study investigates how cryptocurrency can be an alternative source of investment to include in an investment portfolio. The daily precious metal and cryptocurrency data from 2017 to 2022 was utilised through an ARDL framework to obtain the Cointegration between cryptocurrency, precious metal and across cryptocurrencies. Modern portfolio theory is used to identify the diversification possibilities in this study with different portfolio diversification strategies. The third study clarified the cryptocurrency stakeholders to identify the global perception of cryptocurrency investments. A qualitative method was employed with sentiment analysis, followed by data extractions from the global databases using machine learning algorithms. The study identified the percentage of stakeholder groups' positive, negative, and neutral perceptions of cryptocurrency. The main obstacles hindering cryptocurrency investment growth are the fear of current scams, lack of definitional issues and the absence of a legal framework in some countries. The fourth study included the findings from the first, second and third studies to develop a cryptocurrency predictive model by factoring in macroeconomic variables. Panel data regression with fixed and dynamic effects was employed to analyse the data from 2017 to 2002. The findings suggest the impact of each macroeconomic variable selected in the study for the cryptocurrency price changes while adding more significance to technological variables. The overall findings provide strong support for the portfolio diversification possibilities of cryptocurrencies. Inclusions of the wide range of investment classes, exploring stakeholder perception and highlighting the macroeconomic variables' influence on the cryptocurrency price prediction generate new insights and valuable comparisons about cryptocurrency markets for academia, crypto issuers, investors, government, policymakers, and fund managers to use as an investment and decision-support tools. Keywords: Cryptocurrency, ARDL, Financial Markets, Cointegration, Causality, Portfolio diversification, Precious Metals, Predictive model.
- Description: Doctor of Philosophy
- Authors: Jayawardhana, Asanga
- Date: 2022
- Type: Text , Thesis , PhD
- Full Text:
- Description: This study was motivated by the breakthrough of cryptocurrencies in 2018. The other main reasons behind the motivation are the total market capitalisation of one trillion-dollar diversification possibilities and the lack of preceding scientific research to identify the portfolio diversification possibilities of cryptocurrencies from many angles. Four empirical studies were conducted to provide a holistic view of cryptocurrency as an investment tool. The first study investigated the portfolio diversification possibilities between cryptocurrencies and traditional financial markets. A quantitative method was employed with Cointegration, ARDL bound testing approach, causality, and co-movement testing. Applying Modern portfolio theory to identify the diversification possibilities between the aforementioned markets enabled the study to highlight how investors can reap the benefits of cryptocurrencies. The second study extended the investigation of the portfolio diversification possibilities of cryptocurrency by including precious metals and cryptocurrencies in the same investment basket. Investors switch from traditional investment assets, such as equity and debt market instruments, to precious metal markets to reap benefits. Therefore, this study investigates how cryptocurrency can be an alternative source of investment to include in an investment portfolio. The daily precious metal and cryptocurrency data from 2017 to 2022 was utilised through an ARDL framework to obtain the Cointegration between cryptocurrency, precious metal and across cryptocurrencies. Modern portfolio theory is used to identify the diversification possibilities in this study with different portfolio diversification strategies. The third study clarified the cryptocurrency stakeholders to identify the global perception of cryptocurrency investments. A qualitative method was employed with sentiment analysis, followed by data extractions from the global databases using machine learning algorithms. The study identified the percentage of stakeholder groups' positive, negative, and neutral perceptions of cryptocurrency. The main obstacles hindering cryptocurrency investment growth are the fear of current scams, lack of definitional issues and the absence of a legal framework in some countries. The fourth study included the findings from the first, second and third studies to develop a cryptocurrency predictive model by factoring in macroeconomic variables. Panel data regression with fixed and dynamic effects was employed to analyse the data from 2017 to 2002. The findings suggest the impact of each macroeconomic variable selected in the study for the cryptocurrency price changes while adding more significance to technological variables. The overall findings provide strong support for the portfolio diversification possibilities of cryptocurrencies. Inclusions of the wide range of investment classes, exploring stakeholder perception and highlighting the macroeconomic variables' influence on the cryptocurrency price prediction generate new insights and valuable comparisons about cryptocurrency markets for academia, crypto issuers, investors, government, policymakers, and fund managers to use as an investment and decision-support tools. Keywords: Cryptocurrency, ARDL, Financial Markets, Cointegration, Causality, Portfolio diversification, Precious Metals, Predictive model.
- Description: Doctor of Philosophy
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