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
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- 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.
Formal verification of fraud-resilience in a crowdsourcing consensus protocol
- Afzaal, Hamra, Imran, Muhammad, Janjua, Muhammad
- Authors: Afzaal, Hamra , Imran, Muhammad , Janjua, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Computers & security Vol. 131, no. (2023), p. 103290
- Full Text: false
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- Description: •A Trust and Transactions Chain consensus protocol is proposed for a blockchain-based crowdsourcing system.•Communicating Sequential Programs language is utilized for the formal modeling of the proposed consensus protocol.•The properties of no sybil attack, no eclipse attack, and fraud-resilience are defined through Linear Temporal Logic.•Model checking is employed to ensure the correctness of the proposed consensus protocol.•The formal verification is performed by giving the formal model and properties as input to the Process Analysis Toolkit. [Display omitted] Crowdsourcing has emerged as a promising computing paradigm that utilizes human intelligence to achieve complex tasks, but it encounters several security and trust issues. Blockchain is a potential technology that can resolve most of these issues, however, it is difficult to find an appropriate consensus protocol applicable to crowdsourcing systems. Therefore, this work presents a Trust and Transactions Chain (TTC) consensus protocol built upon blockchain technology. It selects a trusted leader and validators considering a trust model which depends on deposit ratio, block generation and validation rate, and waiting rate. The TTC protocol addresses the main challenge of ensuring correctness related to critical systems of crowdsourcing which has extreme significance as their failure can result in disastrous consequences. This work is primarily focused on fraud-resilience avoiding double-spending attack. It also deals with sybil and eclipse attacks. Model checking is exploited because it is effective and automatic to conduct formal verification. The TTC protocol is formally modeled utilizing Communicating Sequential Programs, and the fraud-resilience property is specified using Linear Temporal Logic. The verification of the model is done using Process Analysis Toolkit that takes the formal model and specified properties as input to inspect the properties’ satisfaction or violation. The results of the formal verification are analyzed with respect to the verification time and the number of visited states.
Malicious node detection using machine learning and distributed data storage using blockchain in WSNs
- Nouman, Muhammad, Qasim, Umar, Nasir, Hina, Almasoud, Abdullah, Imran, Muhammad, Javaid, Nadeem
- Authors: Nouman, Muhammad , Qasim, Umar , Nasir, Hina , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 6106-6121
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- Description: In the proposed work, blockchain is implemented on the Base Stations (BSs) and Cluster Heads (CHs) to register the nodes using their credentials and also to tackle various security issues. Moreover, a Machine Learning (ML) classifier, termed as Histogram Gradient Boost (HGB), is employed on the BSs to classify the nodes as malicious or legitimate. In case, the node is found to be malicious, its registration is revoked from the network. Whereas, if a node is found to be legitimate, then its data is stored in an Interplanetary File System (IPFS). IPFS stores the data in the form of chunks and generates hash for the data, which is then stored in blockchain. In addition, Verifiable Byzantine Fault Tolerance (VBFT) is used instead of Proof of Work (PoW) to perform consensus and validate transactions. Also, extensive simulations are performed using the Wireless Sensor Network (WSN) dataset, referred as WSN-DS. The proposed model is evaluated both on the original dataset and the balanced dataset. Furthermore, HGB is compared with other existing classifiers, Adaptive Boost (AdaBoost), Gradient Boost (GB), Linear Discriminant Analysis (LDA), Extreme Gradient Boost (XGB) and ridge, using different performance metrics like accuracy, precision, recall, micro-F1 score and macro-F1 score. The performance evaluation of HGB shows that it outperforms GB, AdaBoost, LDA, XGB and Ridge by 2-4%, 8-10%, 12-14%, 3-5% and 14-16%, respectively. Moreover, the results with balanced dataset are better than those with original dataset. Also, VBFT performs 20-30% better than PoW. Overall, the proposed model performs efficiently in terms of malicious node detection and secure data storage. © 2013 IEEE.
- Authors: Nouman, Muhammad , Qasim, Umar , Nasir, Hina , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 6106-6121
- Full Text:
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- Description: In the proposed work, blockchain is implemented on the Base Stations (BSs) and Cluster Heads (CHs) to register the nodes using their credentials and also to tackle various security issues. Moreover, a Machine Learning (ML) classifier, termed as Histogram Gradient Boost (HGB), is employed on the BSs to classify the nodes as malicious or legitimate. In case, the node is found to be malicious, its registration is revoked from the network. Whereas, if a node is found to be legitimate, then its data is stored in an Interplanetary File System (IPFS). IPFS stores the data in the form of chunks and generates hash for the data, which is then stored in blockchain. In addition, Verifiable Byzantine Fault Tolerance (VBFT) is used instead of Proof of Work (PoW) to perform consensus and validate transactions. Also, extensive simulations are performed using the Wireless Sensor Network (WSN) dataset, referred as WSN-DS. The proposed model is evaluated both on the original dataset and the balanced dataset. Furthermore, HGB is compared with other existing classifiers, Adaptive Boost (AdaBoost), Gradient Boost (GB), Linear Discriminant Analysis (LDA), Extreme Gradient Boost (XGB) and ridge, using different performance metrics like accuracy, precision, recall, micro-F1 score and macro-F1 score. The performance evaluation of HGB shows that it outperforms GB, AdaBoost, LDA, XGB and Ridge by 2-4%, 8-10%, 12-14%, 3-5% and 14-16%, respectively. Moreover, the results with balanced dataset are better than those with original dataset. Also, VBFT performs 20-30% better than PoW. Overall, the proposed model performs efficiently in terms of malicious node detection and secure data storage. © 2013 IEEE.
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.
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- 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.
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- 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.
A blockchain-based framework for automatic SLA management in fog computing environments
- Battula, Sudheer, Garg, Saurabh, Naha, Ranesh, Amin, Muhammad, Kang, Byeong, Aghasian, Erfan
- Authors: Battula, Sudheer , Garg, Saurabh , Naha, Ranesh , Amin, Muhammad , Kang, Byeong , Aghasian, Erfan
- Date: 2022
- Type: Text , Journal article
- Relation: The Journal of supercomputing Vol. 78, no. 15 (2022), p. 16647-16677
- Full Text: false
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- Description: Fog computing has become a prominent paradigm in providing shared resources to serve different applications near the edge. Similar to other computing paradigms such as cloud and grid, in fog computing, service-level agreements (SLAs) are essential between fog providers and end-users to guarantee the quality of service (QoS). However, due to the unique characteristics of fog resources, such as being highly distributed and heterogeneous, with their dynamic nature having nonrestrictive provider participation, SLA management techniques and frameworks, which are available for Clouds and Grids, are not directly applicable. The availability of the resources in the cloud is much more controllable and predictable compared to fog. Moreover, due to the multiple ownership of fog infrastructure and unrestricted environment, autonomous end-devices are allowed to participate with different SLAs to serve the applications near the edge as a result is a lack of trust exists between the entities and managing and enforcing SLAs according to the application QoS in this environment is a complex task. Thus, the SLA management must be undertaken in a more trustworthy manner to ensure that agreement. To fill this gap, this paper proposes an automated SLA management framework for fog computing that utilizes Smart contracts and blockchain technology to monitor and enforce SLAs in a more trustworthy manner. The results obtained from the experiments, which were conducted in the blockchain private network, show that the framework can ensure precise and efficient SLAs enforcement in the fog. The performance of the proposed framework is better than existing work in terms of transaction cost and time.
A survey of blockchain-based IoT eHealthcare : applications, research issues, and challenges
- Rahman, Md Shafiur, Islam, Md Amirul, Uddin, Md Ashraf, Stea, Giovanni
- Authors: Rahman, Md Shafiur , Islam, Md Amirul , Uddin, Md Ashraf , Stea, Giovanni
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Internet of Things (Netherlands) Vol. 19, no. (2022), p.
- Full Text: false
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- Description: Blockchain (BC) technology has recently emerged as an essential component for different applications, including healthcare and IoT, because of its decentralized ledger, source provenance, and tamper-proof nature. The Internet of Things (IoT) and BC have enabled health systems to expand their scalability and maintain consistency on a decentralized platform. As a result, many researchers have developed BC-enabled IoT eHealth systems and explored the application of BC technology in diverse fields of eHealthcare. This paper conducts a comprehensive survey on the emerging applications of BC technology in healthcare. We summarize applications, research issues, security threats, research challenges, opportunities, and the future scope of BC technologies in the IoT-enabled healthcare system when BC is adopted to handle the privacy and storage of current and future medical records. Furthermore, we analyze the state-of-the-art BC works in the medical area, assessing their benefits-drawbacks, and guiding future researchers to overcome the limitations of the existing articles. © 2022 Elsevier B.V.
An interpretive study of stakeholders privacy issues in blockchain : a healthcare context
- Singh, Supreet, Firmin, Sally, Chadhar, Mehmood
- Authors: Singh, Supreet , Firmin, Sally , Chadhar, Mehmood
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 Australasian Computer Science Week, ACSW 2022, Virtual, Online, 14-17 February 2022, ACM International Conference Proceeding Series p. 235-238
- Full Text: false
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- Description: Ever-growing and rapidly changing healthcare information systems (HIS) encourage many new technologies to integrate with it to enrich the treatment and facilitate patients. Blockchain, a decentralised digital ledger, is legitimately disrupting traditional HIS due to its characteristics such as immutability, interoperability, decentralise, and security. Blockchain' applications in healthcare industries are attracting investors and organisations to develop platforms for future. However, security and privacy concerns hinder blockchain adoption in the health sector. Therefore, there is a need to develop deeper understandings about these issues and require strategies to address these issues so that the desired values can be obtained. Besides, privacy could mean different to different people such as patients, doctors, and admin staff. Therefore, there is a need to explore it from various stakeholder perspectives too. Using interpretive qualitative research approach, this research-in-progress will extend the body of knowledge by scrutinising the stakeholders' perception of privacy concerns and its relationship in blockchain based HIS. The findings of this study will contribute to address privacy issues emerged from the research and help to eliminate them before implementing blockchain. This paper supplies an appropriate research approach for multidimensional research in healthcare. In addition, this research-in progress will formulate a framework which provide awareness to stakeholders about privacy issues when they use blockchain based HIS in future. © 2022 ACM.
Analysis of applying blockchain technology to hospitality operation
- Verma, Anshul, Verma, Pradeepika, Farhaoui, Yousef, Lv, Zhihan
- Authors: Verma, Anshul , Verma, Pradeepika , Farhaoui, Yousef , Lv, Zhihan
- Date: 2022
- Type: Text , Book chapter
- Relation: Emerging Real-World Applications of Internet of Things Chapter 6 p.
- Full Text: false
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- Description: Blockchain was first conceptualised in 2008 and drew attention from the general public since the introduction of one of its applications, cryptocurrency, in 2014. Blockchain consists of several revolutionary characteristics and has already been applied in different industries. Therefore, it is also deemed as a computer technology that has the potential to change the traditional business model. The hospitality industry is one of the significant economic supports to New Zealand; this industry could take advantage of the implementation of blockchain technology. Moreover, applying blockchain technology in various industries is a new arena in the existing research. The results of qualitative research indicate that blockchain technology could benefit the hospitality industry by building a more trustable reputation system, smoothening operation flow, reducing operation cost, enhancing customer experiences, enhancing food safety, and providing convenient payment methods without the necessity of intermediaries. This chapter is focused on investigating how the implementation of blockchain technology benefits the hospitality industry, together with its potential drawbacks.
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
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- 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
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
- Afzaal, Hamra, Imran, Muhammad, Janjua, Muhammad
- Authors: Afzaal, Hamra , Imran, Muhammad , Janjua, Muhammad
- Date: 2022
- Type: Text , Journal article
- Relation: Computer Communications Vol. 192, no. (2022), p. 384-401
- Full Text: false
- Reviewed:
- Description: Crowdsourcing is a potential computing paradigm that exploits collective human intelligence to solve complex tasks, but it suffers from various safety and security problems. Blockchain has emerged as a promising technology to address most of the security issues, however, it is challenging to find an appropriate and trusted blockchain-based consensus protocol for crowdsourcing services. This work proposes a novel Trust-based Blockchain Crowdsourcing consensus protocol that selects a leader and validators based on various trust factors. The proposed protocol addresses a major issue of ensuring correctness associated with the safety and security-critical systems which has a vital importance because failure of such systems may lead to adverse consequences. Mainly it is focused on persistence and liveness properties preventing invalid block insertion and consensus delay attacks. Model checking technique is utilized because of its effectiveness and automatic nature to perform formal verification. The proposed protocol is specified using Communicating Sequential Programs, and the persistence and liveness properties are specified through Linear Temporal Logic. The model verification is performed by giving the formal model and the properties as input to the Process Analysis Toolkit which checks for the satisfaction or violation of the properties. © 2022 Elsevier B.V.
Incorporating price information in Blockchain-based energy trading
- Islam, Ezazul, Chetty, Madhu, Lim, Suryani, Chadhar, Mehmood, Islam, Syed
- Authors: Islam, Ezazul , Chetty, Madhu , Lim, Suryani , Chadhar, Mehmood , Islam, Syed
- Date: 2022
- Type: Text , Conference proceedings
- Relation: SIG SAND -Systems Analysis and Design, 2022; Minneapolis; August 10th-14th, 2022 in AMCIS 2022 Proceedings. 6.
- Full Text: false
- Reviewed:
- Description: Blockchain-based peer-to-peer (P2P) ecosystem is well suited for distributed energy trading as it is inherently decentralised. In a distributed energy trading, an auctioneer passes unspent reservations to the next auctioneer, as dictated by the passing mechanism. However, traditional P2P energy trading systems used passing mechanisms that only partially consider the auction capability of the next auctioneer. We propose iPass, which incorporates price information when passing unspent auction reservations in P2P energy trading environment. The three performance metrics applied to measure the trading efficiency are (a) auction convergence time, (b) the number of auction settlements, and (c) the economic surplus of buyers and sellers. We simulated the proposed mechanism in Hyperledger Fabric, a permissioned blockchain framework. Hyperledger Fabric manages the data storage and smart contracts. Experiments show iPass is more efficient compared to existing passing mechanisms.
Resilience of stablecoin reserve for distributed energy trading
- Islam, Md Ezazul, Chetty, Madhu, Lim, Suryani, Chadhar, Mehmood, Islam, Syed
- Authors: Islam, Md Ezazul , Chetty, Madhu , Lim, Suryani , Chadhar, Mehmood , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 14th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2022, Melbourne, Australia, 20-23 November 2022, Asia-Pacific Power and Energy Engineering Conference, APPEEC Vol. 2022-November
- Full Text: false
- Reviewed:
- Description: For payment settlement, a blockchain-based Peer-To-Peer (P2P) energy trading requires a stable medium of exchange with little price volatility. Stablecoins, the most suitable medium of exchange, gaining concentration even from central banks. A consortium of central banks recommends complying with capital and liquidity standards for the high-quality liquid asset (HQLA) for the solvency of banks or financial institutions. Stablecoin as HQLA requires the adaption of such standards in P2P energy trading for reserve resilience. We propose a mechanism (NF90) that controls the inflow of stablecoins responding to Liquidity Coverage Ratio (LCR) for reserve resilience. Basel III accord recommends 100% of LCR. We measure the efficiency of NF90 concerning LCR as a metric. We simulate the proposed mechanism in Hyperledger Fabric as a permissioned blockchain platform for decentralisation, data storage, and smart contract. Experiments show that NF90 is the most efficient inflow control mechanism compared to other simulated mechanisms. © 2022 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**
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
CRT-BIoV : a cognitive radio technique for blockchain-enabled internet of vehicles
- Rathee, Geetanjali, Ahmad, Farhan, Kurugollu, Fatih, Azad, Muhammad, Iqbal, Razi, Imran, Muhammad
- Authors: Rathee, Geetanjali , Ahmad, Farhan , Kurugollu, Fatih , Azad, Muhammad , Iqbal, Razi , Imran, Muhammad
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Intelligent Transportation Systems Vol. 22, no. 7 (2021), p. 4005-4015
- Full Text: false
- Reviewed:
- Description: Cognitive Radio Network (CRN) is considered as a viable solution on Internet of Vehicle (IoV) where objects equipped with cognition make decisions intelligently through the understanding of both social and physical worlds. However, the spectrum availability and data sharing/transferring among vehicles are critical improving services and driving safety metrics where the presence of Malicious Devices (MD) further degrade the network performance. Recently, a blockchain technique in CRN-based IoV has been introduced to prevent data alteration from these MD and allowing the vehicles to track both legal and illegal activities in the network. In this paper, we provide the security to IoV during spectrum sensing and information transmission using CRN by sensing the channels through a decision-making technique known as Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), a technique that evokes the trust of its Cognitive Users (CU) by analyzing certain predefined attributes. Further, blockchain is maintained in the network to trace every activity of stored information. The proposed mechanism is validated rigorously against several security metrics using various spectrum sensing and security parameters against a baseline solution in IoV. Extensive simulations suggest that our proposed mechanism is approximately 70% more efficient in terms of malicious nodes identification and DoS threat against the baseline mechanism. © 2000-2011 IEEE.
Enhanced profitability of photovoltaic plants by utilizing cryptocurrency-based mining load
- Eid, Bilal, Islam, Md Rabiul, Shah, Rakibuzzaman, Nahid, Abdullah, Kouzani, Abbas, Mahmud, M.
- Authors: Eid, Bilal , Islam, Md Rabiul , Shah, Rakibuzzaman , Nahid, Abdullah , Kouzani, Abbas , Mahmud, M.
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Applied Superconductivity Vol. 31, no. 8 (2021), p.
- Full Text: false
- Reviewed:
- Description: The grid connected photovoltaic (PV) power plants (PVPPs) are booming nowadays. The main problem facing the PV power plants deployment is the intermittency which leads to instability of the grid. In order to stabilize the grid, either energy storage device - mainly batteries - or a power curtailment technique can be used. The additional cost on utilizing batteries make it not preferred solution, because it leads to a drop in the return on investment (ROI) of the project. A good alternative, is using a customized load (such as; cryptocurrency-based loads) which consumes the surplus energy. This paper investigating the usage of a customized load - cryptocurrency mining rig - to create an added value for the owner of the plant and increase the ROI of the project. These devices are widely used to perform the required calculations for validating the transactions on the network of the Blockchain. A comparison between the ROI of the mining rig and the battery have been conducted in this study. Based on this study the mining rig has superior ROI of 7.7% - in the case with the lowest ROI - compared to 4.5% for battery. Moreover, an improved controlling strategy is developed to combine both the battery and mining rig in the same system. The developed strategy is able to keep the profitability as high as possible during the fluctuation of the mining network. © 2002-2011 IEEE.
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.
Is blockchain for internet of medical things a panacea for COVID-19 pandemic?
- Li, Xuran, Tao, Bishenghui, Dai, Hong-Ning, Imran, Muhammad, Wan, Dehuan, Li, Dengwang
- Authors: Li, Xuran , Tao, Bishenghui , Dai, Hong-Ning , Imran, Muhammad , Wan, Dehuan , Li, Dengwang
- Date: 2021
- Type: Text , Journal article
- Relation: Pervasive and Mobile Computing Vol. 75, no. (2021), p.
- Full Text: false
- Reviewed:
- Description: The outbreak of the COVID-19 pandemic has deeply influenced the lifestyle of the general public and the healthcare system of the society. As a promising approach to address the emerging challenges caused by the epidemic of infectious diseases like COVID-19, Internet of Medical Things (IoMT) deployed in hospitals, clinics, and healthcare centers can save the diagnosis time and improve the efficiency of medical resources though privacy and security concerns of IoMT stall the wide adoption. In order to tackle the privacy, security, and interoperability issues of IoMT, we propose a framework of blockchain-enabled IoMT by introducing blockchain to incumbent IoMT systems. In this paper, we review the benefits of this architecture and illustrate the opportunities brought by blockchain-enabled IoMT. We also provide use cases of blockchain-enabled IoMT on fighting against the COVID-19 pandemic, including the prevention of infectious diseases, location sharing and contact tracing, and the supply chain of injectable medicines. We also outline future work in this area. © 2021 Elsevier B.V.