Continuous patient monitoring with a patient centric agent : A block architecture
- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 32700-32726
- Full Text:
- Reviewed:
- Description: The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications, including continuous remote patient monitoring (RPM). However, the complexity of RPM architectures, the size of data sets generated and limited power capacity of devices make RPM challenging. In this paper, we propose a tier-based End to End architecture for continuous patient monitoring that has a patient centric agent (PCA) as its center piece. The PCA manages a blockchain component to preserve privacy when data streaming from body area sensors needs to be stored securely. The PCA based architecture includes a lightweight communication protocol to enforce security of data through different segments of a continuous, real time patient monitoring architecture. The architecture includes the insertion of data into a personal blockchain to facilitate data sharing amongst healthcare professionals and integration into electronic health records while ensuring privacy is maintained. The blockchain is customized for RPM with modifications that include having the PCA select a Miner to reduce computational effort, enabling the PCA to manage multiple blockchains for the same patient, and the modification of each block with a prefix tree to minimize energy consumption and incorporate secure transaction payments. Simulation results demonstrate that security and privacy can be enhanced in RPM with the PCA based End to End architecture.
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 32700-32726
- Full Text:
- Reviewed:
- Description: The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications, including continuous remote patient monitoring (RPM). However, the complexity of RPM architectures, the size of data sets generated and limited power capacity of devices make RPM challenging. In this paper, we propose a tier-based End to End architecture for continuous patient monitoring that has a patient centric agent (PCA) as its center piece. The PCA manages a blockchain component to preserve privacy when data streaming from body area sensors needs to be stored securely. The PCA based architecture includes a lightweight communication protocol to enforce security of data through different segments of a continuous, real time patient monitoring architecture. The architecture includes the insertion of data into a personal blockchain to facilitate data sharing amongst healthcare professionals and integration into electronic health records while ensuring privacy is maintained. The blockchain is customized for RPM with modifications that include having the PCA select a Miner to reduce computational effort, enabling the PCA to manage multiple blockchains for the same patient, and the modification of each block with a prefix tree to minimize energy consumption and incorporate secure transaction payments. Simulation results demonstrate that security and privacy can be enhanced in RPM with the PCA based End to End architecture.
Rapid health data repository allocation using predictive machine learning
- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: Health Informatics Journal Vol. 26, no. 4 (2020), p. 3009-3036
- Full Text:
- Reviewed:
- Description: Health-related data is stored in a number of repositories that are managed and controlled by different entities. For instance, Electronic Health Records are usually administered by governments. Electronic Medical Records are typically controlled by health care providers, whereas Personal Health Records are managed directly by patients. Recently, Blockchain-based health record systems largely regulated by technology have emerged as another type of repository. Repositories for storing health data differ from one another based on cost, level of security and quality of performance. Not only has the type of repositories increased in recent years, but the quantum of health data to be stored has increased. For instance, the advent of wearable sensors that capture physiological signs has resulted in an exponential growth in digital health data. The increase in the types of repository and amount of data has driven a need for intelligent processes to select appropriate repositories as data is collected. However, the storage allocation decision is complex and nuanced. The challenges are exacerbated when health data are continuously streamed, as is the case with wearable sensors. Although patients are not always solely responsible for determining which repository should be used, they typically have some input into this decision. Patients can be expected to have idiosyncratic preferences regarding storage decisions depending on their unique contexts. In this paper, we propose a predictive model for the storage of health data that can meet patient needs and make storage decisions rapidly, in real-time, even with data streaming from wearable sensors. The model is built with a machine learning classifier that learns the mapping between characteristics of health data and features of storage repositories from a training set generated synthetically from correlations evident from small samples of experts. Results from the evaluation demonstrate the viability of the machine learning technique used. © The Author(s) 2020.
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: Health Informatics Journal Vol. 26, no. 4 (2020), p. 3009-3036
- Full Text:
- Reviewed:
- Description: Health-related data is stored in a number of repositories that are managed and controlled by different entities. For instance, Electronic Health Records are usually administered by governments. Electronic Medical Records are typically controlled by health care providers, whereas Personal Health Records are managed directly by patients. Recently, Blockchain-based health record systems largely regulated by technology have emerged as another type of repository. Repositories for storing health data differ from one another based on cost, level of security and quality of performance. Not only has the type of repositories increased in recent years, but the quantum of health data to be stored has increased. For instance, the advent of wearable sensors that capture physiological signs has resulted in an exponential growth in digital health data. The increase in the types of repository and amount of data has driven a need for intelligent processes to select appropriate repositories as data is collected. However, the storage allocation decision is complex and nuanced. The challenges are exacerbated when health data are continuously streamed, as is the case with wearable sensors. Although patients are not always solely responsible for determining which repository should be used, they typically have some input into this decision. Patients can be expected to have idiosyncratic preferences regarding storage decisions depending on their unique contexts. In this paper, we propose a predictive model for the storage of health data that can meet patient needs and make storage decisions rapidly, in real-time, even with data streaming from wearable sensors. The model is built with a machine learning classifier that learns the mapping between characteristics of health data and features of storage repositories from a training set generated synthetically from correlations evident from small samples of experts. Results from the evaluation demonstrate the viability of the machine learning technique used. © The Author(s) 2020.
Blockchain leveraged decentralized IoT eHealth framework
- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: Internet of Things Vol. 9, no. March 2020 p. 100159
- Full Text:
- Reviewed:
- Description: Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data.
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: Internet of Things Vol. 9, no. March 2020 p. 100159
- Full Text:
- Reviewed:
- Description: Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data.
Timeless principles of taxpayer protection: how they adapt to digital disruption
- Authors: Bentley, Duncan
- Date: 2019
- Type: Text , Journal article
- Relation: eJournal of Tax Research Vol. 16, no. 3 (2019), p. 679-713
- Full Text:
- Reviewed:
- Description: Digital transformation will pose growing challenges to tax revenues and systems of taxation that were designed for another century. The tax rules may hasten slowly, but the record of response to the challenges of electronic commerce, and of base erosion and profit shifting, shows that tax administration is more adaptable. This article identifies the detailed nature of technological changes in electronics and systems; big data, automation and artificial intelligence; and security, including blockchain; as those changes affect tax administration. It highlights the critical taxpayer rights issues and applies accepted taxpayer rights frameworks. The article concludes that taxpayer rights principles are both highly adaptable to a digital world, and provide useful guidance to where urgent action and further research are required. © 2019 UNSW Business School™.
- Authors: Bentley, Duncan
- Date: 2019
- Type: Text , Journal article
- Relation: eJournal of Tax Research Vol. 16, no. 3 (2019), p. 679-713
- Full Text:
- Reviewed:
- Description: Digital transformation will pose growing challenges to tax revenues and systems of taxation that were designed for another century. The tax rules may hasten slowly, but the record of response to the challenges of electronic commerce, and of base erosion and profit shifting, shows that tax administration is more adaptable. This article identifies the detailed nature of technological changes in electronics and systems; big data, automation and artificial intelligence; and security, including blockchain; as those changes affect tax administration. It highlights the critical taxpayer rights issues and applies accepted taxpayer rights frameworks. The article concludes that taxpayer rights principles are both highly adaptable to a digital world, and provide useful guidance to where urgent action and further research are required. © 2019 UNSW Business School™.
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 organizational adoption of blockchain technology : extending the technology–organization– environment (TOE) framework in the Australian context
- Malik, Saleem, Chadhar, Mehmood, Vatanasakdakul, Savanid, Chetty, Madhu
- Authors: Malik, Saleem , Chadhar, Mehmood , Vatanasakdakul, Savanid , Chetty, Madhu
- Date: 2021
- Type: Text , Journal article
- Relation: Sustainability (Switzerland) Vol. 13, no. 16 (2021), p.
- Full Text:
- Reviewed:
- Description: Blockchain technology (BCT) has been gaining popularity due to its benefits for almost every industry. However, despite its benefits, the organizational adoption of BCT is rather limited. This lack of uptake motivated us to identify the factors that influence the adoption of BCT from an organizational perspective. In doing this, we reviewed the BCT literature, interviewed BCT experts, and proposed a research model based on the TOE framework. Specifically, we theorized the role of technological (perceived benefits, compatibility, information transparency, and disintermediation), organizational (organization innovativeness, organizational learning capability, and top management support), and environmental (competition intensity, government support, trading partners readiness, and standards uncertainty) factors in the organizational adoption of BCT in Australia. We confirmed the model with a sample of adopters and potential adopter organizations in Aus-tralia. The results show a significant role of the proposed factors in the organizational adoption of BCT in Australia. Additionally, we found that the relationship between the influential factors and BCT adoption is moderated by “perceived risks”. The study extends the TOE framework by adding factors that were ignored in previous studies on BCT adoption, such as perceived information trans-parency, perceived disintermediation, organizational innovativeness, organizational learning capa-bility, and standards uncertainty. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Malik, Saleem , Chadhar, Mehmood , Vatanasakdakul, Savanid , Chetty, Madhu
- Date: 2021
- Type: Text , Journal article
- Relation: Sustainability (Switzerland) Vol. 13, no. 16 (2021), p.
- Full Text:
- Reviewed:
- Description: Blockchain technology (BCT) has been gaining popularity due to its benefits for almost every industry. However, despite its benefits, the organizational adoption of BCT is rather limited. This lack of uptake motivated us to identify the factors that influence the adoption of BCT from an organizational perspective. In doing this, we reviewed the BCT literature, interviewed BCT experts, and proposed a research model based on the TOE framework. Specifically, we theorized the role of technological (perceived benefits, compatibility, information transparency, and disintermediation), organizational (organization innovativeness, organizational learning capability, and top management support), and environmental (competition intensity, government support, trading partners readiness, and standards uncertainty) factors in the organizational adoption of BCT in Australia. We confirmed the model with a sample of adopters and potential adopter organizations in Aus-tralia. The results show a significant role of the proposed factors in the organizational adoption of BCT in Australia. Additionally, we found that the relationship between the influential factors and BCT adoption is moderated by “perceived risks”. The study extends the TOE framework by adding factors that were ignored in previous studies on BCT adoption, such as perceived information trans-parency, perceived disintermediation, organizational innovativeness, organizational learning capa-bility, and standards uncertainty. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Blockchain leveraged task migration in body area sensor networks
- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th Asia-Pacific Conference on Communications, APCC 2019 p. 177-184
- Full Text:
- Reviewed:
- Description: Blockchain technologies emerging for healthcare support secure health data sharing with greater interoperability among different heterogeneous systems. However, the collection and storage of data generated from Body Area Sensor Net-works(BASN) for migration to high processing power computing services requires an efficient BASN architecture. We present a decentralized BASN architecture that involves devices at three levels; 1) Body Area Sensor Network-medical sensors typically on or in patient's body transmitting data to a Smartphone, 2) Fog/Edge, and 3) Cloud. We propose that a Patient Agent(PA) replicated on the Smartphone, Fog and Cloud servers processes medical data and execute a task offloading algorithm by leveraging a Blockchain. Performance analysis is conducted to demonstrate the feasibility of the proposed Blockchain leveraged, distributed Patient Agent controlled BASN. © 2019 IEEE.
- Description: E1
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th Asia-Pacific Conference on Communications, APCC 2019 p. 177-184
- Full Text:
- Reviewed:
- Description: Blockchain technologies emerging for healthcare support secure health data sharing with greater interoperability among different heterogeneous systems. However, the collection and storage of data generated from Body Area Sensor Net-works(BASN) for migration to high processing power computing services requires an efficient BASN architecture. We present a decentralized BASN architecture that involves devices at three levels; 1) Body Area Sensor Network-medical sensors typically on or in patient's body transmitting data to a Smartphone, 2) Fog/Edge, and 3) Cloud. We propose that a Patient Agent(PA) replicated on the Smartphone, Fog and Cloud servers processes medical data and execute a task offloading algorithm by leveraging a Blockchain. Performance analysis is conducted to demonstrate the feasibility of the proposed Blockchain leveraged, distributed Patient Agent controlled BASN. © 2019 IEEE.
- Description: E1
An efficient selective miner consensus protocol in blockchain oriented iot smart monitoring
- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne; Australia; 13th-15th February 2019 Vol. 2019-February, p. 1135-1142
- Full Text:
- Reviewed:
- Description: Blockchains have been widely used in Internet of Things(IoT) applications including smart cities, smart home and smart governance to provide high levels of security and privacy. In this article, we advance a Blockchain based decentralized architecture for the storage of IoT data produced from smart home/cities. The architecture includes a secure communication protocol using a sign-encryption technique between power constrained IoT devices and a Gateway. The sign encryption also preserves privacy. We propose that a Software Agent executing on the Gateway selects a Miner node using performance parameters of Miners. Simulations demonstrate that the recommended Miner selection outperforms Proof of Works selection used in Bitcoin and Random Miner Selection.
- Description: Proceedings of the IEEE International Conference on Industrial Technology
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne; Australia; 13th-15th February 2019 Vol. 2019-February, p. 1135-1142
- Full Text:
- Reviewed:
- Description: Blockchains have been widely used in Internet of Things(IoT) applications including smart cities, smart home and smart governance to provide high levels of security and privacy. In this article, we advance a Blockchain based decentralized architecture for the storage of IoT data produced from smart home/cities. The architecture includes a secure communication protocol using a sign-encryption technique between power constrained IoT devices and a Gateway. The sign encryption also preserves privacy. We propose that a Software Agent executing on the Gateway selects a Miner node using performance parameters of Miners. Simulations demonstrate that the recommended Miner selection outperforms Proof of Works selection used in Bitcoin and Random Miner Selection.
- Description: Proceedings of the IEEE International Conference on Industrial Technology
Challenges and opportunities for blockchain technology adoption : a systematic review
- Chhina, Shipra, Chadhar, Mehmood, Vatanasakdakul, Savanid, Chetty, Madhu
- Authors: Chhina, Shipra , Chadhar, Mehmood , Vatanasakdakul, Savanid , Chetty, Madhu
- Date: 2019
- Type: Text , Conference paper
- Relation: 30th Australasian Conference on Information Systems (ACIS), 9-11 December, Perth (Australia)
- Full Text:
- Reviewed:
- Description: Blockchain technology promises to significantly impact current business processes in industries from various sectors and reduce transactional cost. Firms, suppliers, government, financial institutions etc. are anticipating a business model transformation through blockchain by accomplishing a decentralized architecture of interorganizational dealings without intermediaries. In spite of its immense potential, however, there are key challenges of blockchain implementation which need to be studied for identifying the opportunities arising and for its successful implementations in future. In this paper, we aim to identify these challenges for blockchain adoption and classify them for clearer understanding. To pursue this effectively, this paper follows a hybrid model of systematic literature review. This paper also explicitly enumerates future research opportunities to lead industry and researchers in correct directions
- Authors: Chhina, Shipra , Chadhar, Mehmood , Vatanasakdakul, Savanid , Chetty, Madhu
- Date: 2019
- Type: Text , Conference paper
- Relation: 30th Australasian Conference on Information Systems (ACIS), 9-11 December, Perth (Australia)
- Full Text:
- Reviewed:
- Description: Blockchain technology promises to significantly impact current business processes in industries from various sectors and reduce transactional cost. Firms, suppliers, government, financial institutions etc. are anticipating a business model transformation through blockchain by accomplishing a decentralized architecture of interorganizational dealings without intermediaries. In spite of its immense potential, however, there are key challenges of blockchain implementation which need to be studied for identifying the opportunities arising and for its successful implementations in future. In this paper, we aim to identify these challenges for blockchain adoption and classify them for clearer understanding. To pursue this effectively, this paper follows a hybrid model of systematic literature review. This paper also explicitly enumerates future research opportunities to lead industry and researchers in correct directions
Novel one time signatures (NOTS) : a compact post-quantum digital signature scheme
- Shahid, Furqan, Ahmad, Iftikhar, Imran, Muhammad, Shoaib, Muhammad
- Authors: Shahid, Furqan , Ahmad, Iftikhar , Imran, Muhammad , Shoaib, Muhammad
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE access Vol. 8, no. (2020), p. 15895-15906
- Full Text:
- Reviewed:
- Description: The future of the hash based digital signature schemes appears to be very bright in the upcoming quantum era because of the quantum threats to the number theory based digital signature schemes. The Shor's algorithm is available to allow a sufficiently powerful quantum computer to break the building blocks of the number theory based signature schemes in a polynomial time. The hash based signature schemes being quite efficient and provably secure can fill in the gap effectively. However, a draw back of the hash based signature schemes is the larger key and signature sizes which can prove a barrier in their adoption by the space critical applications, like the blockchain. A hash based signature scheme is constructed using a one time signature (OTS) scheme. The underlying OTS scheme plays an important role in determining key and signature sizes of a hash based signature scheme. In this article, we have proposed a novel OTS scheme with minimized key and signature sizes as compared to all of the existing OTS schemes. Our proposed OTS scheme offers an 88% reduction in both key and signature sizes as compared to the popular Winternitz OTS scheme. Furthermore, our proposed OTS scheme offers an 84% and an 86% reductions in the signature and the key sizes respectively as compared to an existing compact variant of the WOTS scheme, i.e. WOTS + .
- Authors: Shahid, Furqan , Ahmad, Iftikhar , Imran, Muhammad , Shoaib, Muhammad
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE access Vol. 8, no. (2020), p. 15895-15906
- Full Text:
- Reviewed:
- Description: The future of the hash based digital signature schemes appears to be very bright in the upcoming quantum era because of the quantum threats to the number theory based digital signature schemes. The Shor's algorithm is available to allow a sufficiently powerful quantum computer to break the building blocks of the number theory based signature schemes in a polynomial time. The hash based signature schemes being quite efficient and provably secure can fill in the gap effectively. However, a draw back of the hash based signature schemes is the larger key and signature sizes which can prove a barrier in their adoption by the space critical applications, like the blockchain. A hash based signature scheme is constructed using a one time signature (OTS) scheme. The underlying OTS scheme plays an important role in determining key and signature sizes of a hash based signature scheme. In this article, we have proposed a novel OTS scheme with minimized key and signature sizes as compared to all of the existing OTS schemes. Our proposed OTS scheme offers an 88% reduction in both key and signature sizes as compared to the popular Winternitz OTS scheme. Furthermore, our proposed OTS scheme offers an 84% and an 86% reductions in the signature and the key sizes respectively as compared to an existing compact variant of the WOTS scheme, i.e. WOTS + .
6G wireless systems : a vision, architectural elements, and future directions
- Khan, Latif, Yaqoob, Ibrar, Imran, Muhammad, Han, Zhu, Hong, Choong
- Authors: Khan, Latif , Yaqoob, Ibrar , Imran, Muhammad , Han, Zhu , Hong, Choong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 147029-147044
- Full Text:
- Reviewed:
- Description: Internet of everything (IoE)-based smart services are expected to gain immense popularity in the future, which raises the need for next-generation wireless networks. Although fifth-generation (5G) networks can support various IoE services, they might not be able to completely fulfill the requirements of novel applications. Sixth-generation (6G) wireless systems are envisioned to overcome 5G network limitations. In this article, we explore recent advances made toward enabling 6G systems. We devise a taxonomy based on key enabling technologies, use cases, emerging machine learning schemes, communication technologies, networking technologies, and computing technologies. Furthermore, we identify and discuss open research challenges, such as artificial-intelligence-based adaptive transceivers, intelligent wireless energy harvesting, decentralized and secure business models, intelligent cell-less architecture, and distributed security models. We propose practical guidelines including deep Q-learning and federated learning-based transceivers, blockchain-based secure business models, homomorphic encryption, and distributed-ledger-based authentication schemes to cope with these challenges. Finally, we outline and recommend several future directions. © 2013 IEEE.
- Authors: Khan, Latif , Yaqoob, Ibrar , Imran, Muhammad , Han, Zhu , Hong, Choong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 147029-147044
- Full Text:
- Reviewed:
- Description: Internet of everything (IoE)-based smart services are expected to gain immense popularity in the future, which raises the need for next-generation wireless networks. Although fifth-generation (5G) networks can support various IoE services, they might not be able to completely fulfill the requirements of novel applications. Sixth-generation (6G) wireless systems are envisioned to overcome 5G network limitations. In this article, we explore recent advances made toward enabling 6G systems. We devise a taxonomy based on key enabling technologies, use cases, emerging machine learning schemes, communication technologies, networking technologies, and computing technologies. Furthermore, we identify and discuss open research challenges, such as artificial-intelligence-based adaptive transceivers, intelligent wireless energy harvesting, decentralized and secure business models, intelligent cell-less architecture, and distributed security models. We propose practical guidelines including deep Q-learning and federated learning-based transceivers, blockchain-based secure business models, homomorphic encryption, and distributed-ledger-based authentication schemes to cope with these challenges. Finally, we outline and recommend several future directions. © 2013 IEEE.
Security and privacy aspects of cloud computing : a smart campus case study
- Gill, Sajid, Razzaq, Mirza, Ahmad, Muneer, Almansour, Fahad, Haq, Ikram
- Authors: Gill, Sajid , Razzaq, Mirza , Ahmad, Muneer , Almansour, Fahad , Haq, Ikram
- Date: 2022
- Type: Text , Journal article
- Relation: Intelligent Automation and Soft Computing Vol. 31, no. 1 (2022), p. 117-128
- Full Text:
- Reviewed:
- Description: The trend of cloud computing is accelerating along with emerging technologies such as utility computing, grid computing, and distributed computing. Cloud computing is showing remarkable potential to provide flexible, cost- effective, and powerful resources across the internet, and is a driving force in today’s most prominent computing technologies. The cloud offers the means to remotely access and store data while virtual machines access data over a network resource. Furthermore, cloud computing plays a leading role in the fourth industrial revolution. Everyone uses the cloud daily life when accessing Dropbox, various Google services, and Microsoft Office 365. While there are many advantages in such an environment, security issues such as data privacy, data security, access control, cyber-attacks, and data availability, along with performance and reliability issues, exist. Efficient security and privacy measures should be implemented by cloud service providers to ensure the privacy, confidentiality, integrity, and availability of data services. However, cloud service providers have not been providing enough secure and reliable services to end users. Blockchain is a technology that is improving cloud computing. This revolutionary technology offers persuasive data integrity properties and is used to tackle security problems. This research presents a detailed analysis of privacy and security challenges in the cloud. We demonstrate the importance of security challenges in a case study in the context of smart campus security, which will encourage researchers to examine security issues in cloud computing in the future. © 2022, Tech Science Press. All rights reserved. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Ikram Haq” is provided in this record**
- Authors: Gill, Sajid , Razzaq, Mirza , Ahmad, Muneer , Almansour, Fahad , Haq, Ikram
- Date: 2022
- Type: Text , Journal article
- Relation: Intelligent Automation and Soft Computing Vol. 31, no. 1 (2022), p. 117-128
- Full Text:
- Reviewed:
- Description: The trend of cloud computing is accelerating along with emerging technologies such as utility computing, grid computing, and distributed computing. Cloud computing is showing remarkable potential to provide flexible, cost- effective, and powerful resources across the internet, and is a driving force in today’s most prominent computing technologies. The cloud offers the means to remotely access and store data while virtual machines access data over a network resource. Furthermore, cloud computing plays a leading role in the fourth industrial revolution. Everyone uses the cloud daily life when accessing Dropbox, various Google services, and Microsoft Office 365. While there are many advantages in such an environment, security issues such as data privacy, data security, access control, cyber-attacks, and data availability, along with performance and reliability issues, exist. Efficient security and privacy measures should be implemented by cloud service providers to ensure the privacy, confidentiality, integrity, and availability of data services. However, cloud service providers have not been providing enough secure and reliable services to end users. Blockchain is a technology that is improving cloud computing. This revolutionary technology offers persuasive data integrity properties and is used to tackle security problems. This research presents a detailed analysis of privacy and security challenges in the cloud. We demonstrate the importance of security challenges in a case study in the context of smart campus security, which will encourage researchers to examine security issues in cloud computing in the future. © 2022, Tech Science Press. All rights reserved. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Ikram Haq” is provided in this record**
Blockchain-based data privacy management with Nudge theory in open banking
- Wang, Hao, Ma, Shenglan, Dai, Hong-Ning, Imran, Muhammad, Wang, Tongsen
- Authors: Wang, Hao , Ma, Shenglan , Dai, Hong-Ning , Imran, Muhammad , Wang, Tongsen
- Date: 2020
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 110, no. (2020), p. 812-823
- Full Text:
- Reviewed:
- Description: Open banking brings both opportunities and challenges to banks all over the world especially in data management. A blockchain as a continuously growing list of records managed by a peer-to-peer network is widely used in various application scenarios; and it is commonly agreed that the blockchain technology can improve the protection of financial data privacy. However, current blockchain technology still poses some challenges in fully meeting the needs of financial data privacy protection. In order to address the existing problems, this paper proposes a new data privacy management framework based on the blockchain technology for the financial sector. The framework consists of three components: (1) a data privacy classification method according to the characteristics of financial data; (2) a new collaborative-filtering-based model; and (3) a data disclosure confirmation scheme for customer strategies based on the Nudge Theory. We implement a prototype and propose a set of algorithms for this framework. The framework is validated through field experiments and laboratory experiments. © 2019 Elsevier B.V.
- Authors: Wang, Hao , Ma, Shenglan , Dai, Hong-Ning , Imran, Muhammad , Wang, Tongsen
- Date: 2020
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 110, no. (2020), p. 812-823
- Full Text:
- Reviewed:
- Description: Open banking brings both opportunities and challenges to banks all over the world especially in data management. A blockchain as a continuously growing list of records managed by a peer-to-peer network is widely used in various application scenarios; and it is commonly agreed that the blockchain technology can improve the protection of financial data privacy. However, current blockchain technology still poses some challenges in fully meeting the needs of financial data privacy protection. In order to address the existing problems, this paper proposes a new data privacy management framework based on the blockchain technology for the financial sector. The framework consists of three components: (1) a data privacy classification method according to the characteristics of financial data; (2) a new collaborative-filtering-based model; and (3) a data disclosure confirmation scheme for customer strategies based on the Nudge Theory. We implement a prototype and propose a set of algorithms for this framework. The framework is validated through field experiments and laboratory experiments. © 2019 Elsevier B.V.
Investigating smart home security : is blockchain the answer?
- Arif, Samrah, Khan, M. Arif, Rehman, Sabih, Kabir, Muhammad, Imran, Muhammad
- Authors: Arif, Samrah , Khan, M. Arif , Rehman, Sabih , Kabir, Muhammad , Imran, Muhammad
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 117802-117816
- Full Text:
- Reviewed:
- Description: Smart Home automation is increasingly gaining popularity among current applications of Internet of Things (IoT) due to the convenience and facilities it provides to the home owners. Sensors are employed within the home appliances via wireless connectivity to be accessible remotely by home owners to operate these devices. With the exponential increase of smart home IoT devices in the marketplace such as door locks, light bulbs, power switches etc, numerous security concerns are arising due to limited storage and processing power of such devices, making these devices vulnerable to several attacks. Due to this reason, security implementations in the deployment of these devices has gained popularity among researchers as a critical research area. Moreover, the adoption of traditional security schemes has failed to address the unique security concerns associated with these devices. Blockchain, a decentralised database based on cryptographic techniques, is gaining enormous attention to assure security of IoT systems. The blockchain framework within an IoT system is a fascinating substitute to the traditional centralised models, which has some significant concerns in fulfilling the demand of smart homes security. In this article, we aim to examine the security of smart homes by instigating the adoption of blockchain and exploring some of the currently proposed smart home architectures using blockchain technology. To present our findings, we describe a simple secure smart home framework based on a refined version of blockchain called Consortium blockchain. We highlight the limitations and opportunities of adopting such an architecture. We further evaluate our model and conclude with the results by designing an experimental testbed using a few household IoT devices commonly available in the marketplace. © 2013 IEEE.
- Authors: Arif, Samrah , Khan, M. Arif , Rehman, Sabih , Kabir, Muhammad , Imran, Muhammad
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 117802-117816
- Full Text:
- Reviewed:
- Description: Smart Home automation is increasingly gaining popularity among current applications of Internet of Things (IoT) due to the convenience and facilities it provides to the home owners. Sensors are employed within the home appliances via wireless connectivity to be accessible remotely by home owners to operate these devices. With the exponential increase of smart home IoT devices in the marketplace such as door locks, light bulbs, power switches etc, numerous security concerns are arising due to limited storage and processing power of such devices, making these devices vulnerable to several attacks. Due to this reason, security implementations in the deployment of these devices has gained popularity among researchers as a critical research area. Moreover, the adoption of traditional security schemes has failed to address the unique security concerns associated with these devices. Blockchain, a decentralised database based on cryptographic techniques, is gaining enormous attention to assure security of IoT systems. The blockchain framework within an IoT system is a fascinating substitute to the traditional centralised models, which has some significant concerns in fulfilling the demand of smart homes security. In this article, we aim to examine the security of smart homes by instigating the adoption of blockchain and exploring some of the currently proposed smart home architectures using blockchain technology. To present our findings, we describe a simple secure smart home framework based on a refined version of blockchain called Consortium blockchain. We highlight the limitations and opportunities of adopting such an architecture. We further evaluate our model and conclude with the results by designing an experimental testbed using a few household IoT devices commonly available in the marketplace. © 2013 IEEE.
Security and privacy in IoT using machine learning and blockchain : threats and countermeasures
- Waheed, Nazar, He, Xiangjian, Ikram, Muhammad, Usman, Muhammad, Hashmi, Saad
- Authors: Waheed, Nazar , He, Xiangjian , Ikram, Muhammad , Usman, Muhammad , Hashmi, Saad
- Date: 2021
- Type: Text , Journal article , Review
- Relation: ACM Computing Surveys Vol. 53, no. 6 (2021), p.
- Full Text:
- Reviewed:
- Description: Security and privacy of users have become significant concerns due to the involvement of the Internet of Things (IoT) devices in numerous applications. Cyber threats are growing at an explosive pace making the existing security and privacy measures inadequate. Hence, everyone on the Internet is a product for hackers. Consequently, Machine Learning (ML) algorithms are used to produce accurate outputs from large complex databases, where the generated outputs can be used to predict and detect vulnerabilities in IoT-based systems. Furthermore, Blockchain (BC) techniques are becoming popular in modern IoT applications to solve security and privacy issues. Several studies have been conducted on either ML algorithms or BC techniques. However, these studies target either security or privacy issues using ML algorithms or BC techniques, thus posing a need for a combined survey on efforts made in recent years addressing both security and privacy issues using ML algorithms and BC techniques. In this article, we provide a summary of research efforts made in the past few years, from 2008 to 2019, addressing security and privacy issues using ML algorithms and BC techniques in the IoT domain. First, we discuss and categorize various security and privacy threats reported in the past 12 years in the IoT domain. We then classify the literature on security and privacy efforts based on ML algorithms and BC techniques in the IoT domain. Finally, we identify and illuminate several challenges and future research directions using ML algorithms and BC techniques to address security and privacy issues in the IoT domain. © 2020 ACM.
- Authors: Waheed, Nazar , He, Xiangjian , Ikram, Muhammad , Usman, Muhammad , Hashmi, Saad
- Date: 2021
- Type: Text , Journal article , Review
- Relation: ACM Computing Surveys Vol. 53, no. 6 (2021), p.
- Full Text:
- Reviewed:
- Description: Security and privacy of users have become significant concerns due to the involvement of the Internet of Things (IoT) devices in numerous applications. Cyber threats are growing at an explosive pace making the existing security and privacy measures inadequate. Hence, everyone on the Internet is a product for hackers. Consequently, Machine Learning (ML) algorithms are used to produce accurate outputs from large complex databases, where the generated outputs can be used to predict and detect vulnerabilities in IoT-based systems. Furthermore, Blockchain (BC) techniques are becoming popular in modern IoT applications to solve security and privacy issues. Several studies have been conducted on either ML algorithms or BC techniques. However, these studies target either security or privacy issues using ML algorithms or BC techniques, thus posing a need for a combined survey on efforts made in recent years addressing both security and privacy issues using ML algorithms and BC techniques. In this article, we provide a summary of research efforts made in the past few years, from 2008 to 2019, addressing security and privacy issues using ML algorithms and BC techniques in the IoT domain. First, we discuss and categorize various security and privacy threats reported in the past 12 years in the IoT domain. We then classify the literature on security and privacy efforts based on ML algorithms and BC techniques in the IoT domain. Finally, we identify and illuminate several challenges and future research directions using ML algorithms and BC techniques to address security and privacy issues in the IoT domain. © 2020 ACM.
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
Edge computing for Internet of Everything : a survey
- Kong, Xiangjie, Wu, Yuhan, Wang, Hui, Xia, Feng
- Authors: Kong, Xiangjie , Wu, Yuhan , Wang, Hui , Xia, Feng
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Internet of Things Journal Vol. 9, no. 23 (2022), p. 23472-23485
- Full Text:
- Reviewed:
- Description: In this era of the Internet of Everything (IoE), edge computing has emerged as the critical enabling technology to solve a series of issues caused by an increasing amount of interconnected devices and large-scale data transmission. However, the deficiencies of edge computing paradigm are gradually being magnified in the context of IoE, especially in terms of service migration, security and privacy preservation, and deployment issues of edge node. These issues can not be well addressed by conventional approaches. Thanks to the rapid development of upcoming technologies, such as artificial intelligence (AI), blockchain, and microservices, novel and more effective solutions have emerged and been applied to solve existing challenges. In addition, edge computing can be deeply integrated with technologies in other domains (e.g., AI, blockchain, 6G, and digital twin) through interdisciplinary intersection and practice, releasing the potential for mutual benefit. These promising integrations need to be further explored and researched. In addition, edge computing provides strong support in applications scenarios, such as remote working, new physical retail industries, and digital advertising, which has greatly changed the way we live, work, and study. In this article, we present an up-to-date survey of the edge computing research. In addition to introducing the definition, model, and characteristics of edge computing, we discuss a set of key issues in edge computing and novel solutions supported by emerging technologies in IoE era. Furthermore, we explore the potential and promising trends from the perspective of technology integration. Finally, new application scenarios and the final form of edge computing are discussed. © 2014 IEEE.
- Authors: Kong, Xiangjie , Wu, Yuhan , Wang, Hui , Xia, Feng
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Internet of Things Journal Vol. 9, no. 23 (2022), p. 23472-23485
- Full Text:
- Reviewed:
- Description: In this era of the Internet of Everything (IoE), edge computing has emerged as the critical enabling technology to solve a series of issues caused by an increasing amount of interconnected devices and large-scale data transmission. However, the deficiencies of edge computing paradigm are gradually being magnified in the context of IoE, especially in terms of service migration, security and privacy preservation, and deployment issues of edge node. These issues can not be well addressed by conventional approaches. Thanks to the rapid development of upcoming technologies, such as artificial intelligence (AI), blockchain, and microservices, novel and more effective solutions have emerged and been applied to solve existing challenges. In addition, edge computing can be deeply integrated with technologies in other domains (e.g., AI, blockchain, 6G, and digital twin) through interdisciplinary intersection and practice, releasing the potential for mutual benefit. These promising integrations need to be further explored and researched. In addition, edge computing provides strong support in applications scenarios, such as remote working, new physical retail industries, and digital advertising, which has greatly changed the way we live, work, and study. In this article, we present an up-to-date survey of the edge computing research. In addition to introducing the definition, model, and characteristics of edge computing, we discuss a set of key issues in edge computing and novel solutions supported by emerging technologies in IoE era. Furthermore, we explore the potential and promising trends from the perspective of technology integration. Finally, new application scenarios and the final form of edge computing are discussed. © 2014 IEEE.
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
Securing smart healthcare cyber-physical systems against blackhole and greyhole attacks using a blockchain-enabled gini index framework
- Javed, Mannan, Tariq, Noshina, Ashraf, Muhammad, Khan, Farrukh, Asim, Muhammad, Imran, Muhammad
- Authors: Javed, Mannan , Tariq, Noshina , Ashraf, Muhammad , Khan, Farrukh , Asim, Muhammad , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 23 (2023), p.
- Full Text:
- Reviewed:
- Description: The increasing reliance on cyber-physical systems (CPSs) in critical domains such as healthcare, smart grids, and intelligent transportation systems necessitates robust security measures to protect against cyber threats. Among these threats, blackhole and greyhole attacks pose significant risks to the availability and integrity of CPSs. The current detection and mitigation approaches often struggle to accurately differentiate between legitimate and malicious behavior, leading to ineffective protection. This paper introduces Gini-index and blockchain-based Blackhole/Greyhole RPL (GBG-RPL), a novel technique designed for efficient detection and mitigation of blackhole and greyhole attacks in smart health monitoring CPSs. GBG-RPL leverages the analytical prowess of the Gini index and the security advantages of blockchain technology to protect these systems against sophisticated threats. This research not only focuses on identifying anomalous activities but also proposes a resilient framework that ensures the integrity and reliability of the monitored data. GBG-RPL achieves notable improvements as compared to another state-of-the-art technique referred to as BCPS-RPL, including a 7.18% reduction in packet loss ratio, an 11.97% enhancement in residual energy utilization, and a 19.27% decrease in energy consumption. Its security features are also very effective, boasting a 10.65% improvement in attack-detection rate and an 18.88% faster average attack-detection time. GBG-RPL optimizes network management by exhibiting a 21.65% reduction in message overhead and a 28.34% decrease in end-to-end delay, thus showing its potential for enhanced reliability, efficiency, and security. © 2023 by the authors.
- Authors: Javed, Mannan , Tariq, Noshina , Ashraf, Muhammad , Khan, Farrukh , Asim, Muhammad , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 23 (2023), p.
- Full Text:
- Reviewed:
- Description: The increasing reliance on cyber-physical systems (CPSs) in critical domains such as healthcare, smart grids, and intelligent transportation systems necessitates robust security measures to protect against cyber threats. Among these threats, blackhole and greyhole attacks pose significant risks to the availability and integrity of CPSs. The current detection and mitigation approaches often struggle to accurately differentiate between legitimate and malicious behavior, leading to ineffective protection. This paper introduces Gini-index and blockchain-based Blackhole/Greyhole RPL (GBG-RPL), a novel technique designed for efficient detection and mitigation of blackhole and greyhole attacks in smart health monitoring CPSs. GBG-RPL leverages the analytical prowess of the Gini index and the security advantages of blockchain technology to protect these systems against sophisticated threats. This research not only focuses on identifying anomalous activities but also proposes a resilient framework that ensures the integrity and reliability of the monitored data. GBG-RPL achieves notable improvements as compared to another state-of-the-art technique referred to as BCPS-RPL, including a 7.18% reduction in packet loss ratio, an 11.97% enhancement in residual energy utilization, and a 19.27% decrease in energy consumption. Its security features are also very effective, boasting a 10.65% improvement in attack-detection rate and an 18.88% faster average attack-detection time. GBG-RPL optimizes network management by exhibiting a 21.65% reduction in message overhead and a 28.34% decrease in end-to-end delay, thus showing its potential for enhanced reliability, efficiency, and security. © 2023 by the authors.
Device agent assisted blockchain leveraged framework for Internet of Things
- Nasrullah, Tarique, Islam, Md Manowarul, Uddin, Md Ashraf, Khan, Md Anisauzzaman, Layek, Md Abu, Stranieri, Andrew, Huh, Eui-Nam
- Authors: Nasrullah, Tarique , Islam, Md Manowarul , Uddin, Md Ashraf , Khan, Md Anisauzzaman , Layek, Md Abu , Stranieri, Andrew , Huh, Eui-Nam
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 1254-1268
- Full Text:
- Reviewed:
- Description: Blockchain (BC) is a burgeoning technology that has emerged as a promising solution to peer-to-peer communication security and privacy challenges. As a revolutionary technology, blockchain has drawn the attention of academics and researchers. Cryptocurrencies have already effectively utilized BC technology. Many researchers have sought to implement this technique in different sectors, including the Internet of Things. To store and manage IoT data, we present in this paper a lightweight BC-based architecture with a modified raft algorithm-based consensus protocol. We designed a Device Agent that executes a novel registration procedure to connect IoT devices to the blockchain. We implemented the framework on Docker using the Go programming language. We have simulated the framework on a Linux environment hosted in the cloud. We have conducted a detailed performance analysis using a variety of measures. The results demonstrate that our suggested solution is suitable for facilitating the management of IoT data with increased security and privacy. In terms of throughput and block generation time, the results indicate that our solution might be 40% to 45% faster than the existing blockchain. © 2013 IEEE.
- Authors: Nasrullah, Tarique , Islam, Md Manowarul , Uddin, Md Ashraf , Khan, Md Anisauzzaman , Layek, Md Abu , Stranieri, Andrew , Huh, Eui-Nam
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 1254-1268
- Full Text:
- Reviewed:
- Description: Blockchain (BC) is a burgeoning technology that has emerged as a promising solution to peer-to-peer communication security and privacy challenges. As a revolutionary technology, blockchain has drawn the attention of academics and researchers. Cryptocurrencies have already effectively utilized BC technology. Many researchers have sought to implement this technique in different sectors, including the Internet of Things. To store and manage IoT data, we present in this paper a lightweight BC-based architecture with a modified raft algorithm-based consensus protocol. We designed a Device Agent that executes a novel registration procedure to connect IoT devices to the blockchain. We implemented the framework on Docker using the Go programming language. We have simulated the framework on a Linux environment hosted in the cloud. We have conducted a detailed performance analysis using a variety of measures. The results demonstrate that our suggested solution is suitable for facilitating the management of IoT data with increased security and privacy. In terms of throughput and block generation time, the results indicate that our solution might be 40% to 45% faster than the existing blockchain. © 2013 IEEE.