Ian Zhou | University of Technology Sydney (original) (raw)

Papers by Ian Zhou

2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS)

As a tool for human technological advancement, the peer-review system acts as a gateway for ensur... more As a tool for human technological advancement, the peer-review system acts as a gateway for ensuring academic paper qualities. However, the system has proven to be slow and expensive. Also, biasedness remains an unsolved problem. Such issues could become a major bottleneck, which can adversely impact research progress and dissemination of knowledge. This paper aims to propose a double-blind paper review system to preserve the authors and reviewers anonymity. This system also addresses issues concerning the reviewers payment, inconsistent review metrics, and biased reviews. The proposed solution utilizes the Hyperledger Fabric blockchain with the InterPlanetary File System (IPFS). The blockchain smart contracts provide a base for financial transactions between paper publishers and the reviewers. Hence, we introduce AcadCoin, a novel cryptocurrency used for supporting said financial transactions. Also, the Hyperledger blockchain provides user access control to achieve double-blindness in reviews. Along with the Hyperledger blockchain, the IPFS is used to store the paper documents, review documents and open metrics documents to reduce the storage requirement of the blockchain. A broad system architecture is constructed to combine the blockchain and the file storage system. This system architecture distributes nodes of the system to related parties. Finally, the blockchain network is implemented and tested using the Hyperledger Composer Playground environment.

The weather phenomenon of frost poses great threats to agriculture. Since it damages the crops an... more The weather phenomenon of frost poses great threats to agriculture. Since it damages the crops and plants from upstream of the supply chain, the potential impact of frosts is significant for agriculture-related industries. As recent frost prediction methods are based on on-site historical data and sensors, extra development and deployment time are required for data collection in any new site. The aim of this article is to eliminate the dependency on on-site historical data and sensors for frost prediction methods. In this article, a frost prediction method based on spatial interpolation is proposed. The models use climate data from existing weather stations, digital elevation models surveys, and normalized difference vegetation index data to estimate a target site's next hour minimum temperature. The proposed method utilizes ensemble learning to increase the model accuracy. Ensemble methods include averaging and weighted averaging. Climate datasets are obtained from 75 weather stations across New South Wales and Australian Capital Territory areas of Australia. The models are constructed with five-fold validation, splitting the weather stations into five testing dataset folds. For each fold, the other stations act as training datasets. After the models are constructed, three experiments are conducted. The first experiment compares the results generated by models between different folds. Then, the second experiment compares the accuracy of different methods. The final experiment reveals the effect of available stations on the proposed models. The results show that the proposed method reached a detection rate up to 92.55%. This method could be implemented as an alternative solution when on-site historical datasets are scarce.

Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, 2019

The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health... more The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health, e-commerce, smart cities, supply chain management, smart cars, cyber-physical systems and a lot more. However, the data collected and processed by IoT systems especially the ones with centralized control are vulnerable to availability, integrity, and privacy threats. Hence, we present "PrivySharing," a blockchain-based innovative framework for integrity and privacy-preserving IoT data sharing in a smart city environment. The proposed scheme is distinct from existing technologies on many aspects. The data privacy is preserved by dividing the blockchain network into various channels, where every channel processes a specific type of data such as health, smart car, smart energy or financial data. Moreover, access to user data within a channel is controlled by embedding access control rules in the smart contracts. In addition, users' data within a channel is further isolated and secured by using private data collection. Likewise, the REST API that enables clients to interact with the blockchain network has dual security in the form of an API Key and OAuth 2.0. The proposed solution also conforms to some of the significant requirements outlined in the European Union General Data Protection Regulation. Lastly, we present a system of reward in the form of a digital token "PrivyCoin" for the users for sharing their data with the stakeholders/third parties.

2020 IEEE 45th Conference on Local Computer Networks (LCN), 2020

The existing lottery-based consensus algorithms, such as Proof-of-Work, and Proof-of-Stake, are m... more The existing lottery-based consensus algorithms, such as Proof-of-Work, and Proof-of-Stake, are mostly used for blockchain-based financial technology applications. Similarly, the Byzantine Fault Tolerance algorithms do provide consensus finality, yet they are either communications intensive, vulnerable to Denial-of-Service attacks, poorly scalable, or have a low faulty node tolerance level. Moreover, these algorithms are not designed for the Internet of Things systems that require near-real-time transaction confirmation, maximum fault tolerance, and appropriate transaction validation rules. Hence, we propose "Pledge," a unique Proof-of-Honesty based consensus protocol to reduce the possibility of malicious behavior during blockchain consensus. Pledge also introduces the Internet of Things centric transaction validation rules. Initial experimentation shows that Pledge is economical and secure with low communications complexity and low latency in transaction confirmation.

2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2020

Exhibition of malicious behavior during blockchain consensus, threats against reputation systems,... more Exhibition of malicious behavior during blockchain consensus, threats against reputation systems, and high TX latency are significant issues for blockchain-based IoT systems. Hence, to mitigate such challenges we propose "Pledge", a unique Proof-of-Honesty based consensus protocol. Initial experimentation shows that Pledge is economical with low computations and communications complexity and low latency in transaction confirmation.

IEEE Access

Applications and technologies of the Internet of Things are in high demand with the increase of n... more Applications and technologies of the Internet of Things are in high demand with the increase of network devices. With the development of technologies such as 5G, machine learning, edge computing, and Industry 4.0, the Internet of Things has evolved. This survey article discusses the evolution of the Internet of Things and presents the vision for Internet of Things 2.0. The Internet of Things 2.0 development is discussed across seven major fields. These fields are machine learning intelligence, mission critical communication, scalability, energy harvesting-based energy sustainability, interoperability, user friendly IoT, and security. Other than these major fields, the architectural development of the Internet of Things and major types of applications are also reviewed. Finally, this article ends with the vision and current limitations of the Internet of Things in future network environments.

IEEE Internet of Things Journal

2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS)

As a tool for human technological advancement, the peer-review system acts as a gateway for ensur... more As a tool for human technological advancement, the peer-review system acts as a gateway for ensuring academic paper qualities. However, the system has proven to be slow and expensive. Also, biasedness remains an unsolved problem. Such issues could become a major bottleneck, which can adversely impact research progress and dissemination of knowledge. This paper aims to propose a double-blind paper review system to preserve the authors and reviewers anonymity. This system also addresses issues concerning the reviewers payment, inconsistent review metrics, and biased reviews. The proposed solution utilizes the Hyperledger Fabric blockchain with the InterPlanetary File System (IPFS). The blockchain smart contracts provide a base for financial transactions between paper publishers and the reviewers. Hence, we introduce AcadCoin, a novel cryptocurrency used for supporting said financial transactions. Also, the Hyperledger blockchain provides user access control to achieve double-blindness in reviews. Along with the Hyperledger blockchain, the IPFS is used to store the paper documents, review documents and open metrics documents to reduce the storage requirement of the blockchain. A broad system architecture is constructed to combine the blockchain and the file storage system. This system architecture distributes nodes of the system to related parties. Finally, the blockchain network is implemented and tested using the Hyperledger Composer Playground environment.

The weather phenomenon of frost poses great threats to agriculture. Since it damages the crops an... more The weather phenomenon of frost poses great threats to agriculture. Since it damages the crops and plants from upstream of the supply chain, the potential impact of frosts is significant for agriculture-related industries. As recent frost prediction methods are based on on-site historical data and sensors, extra development and deployment time are required for data collection in any new site. The aim of this article is to eliminate the dependency on on-site historical data and sensors for frost prediction methods. In this article, a frost prediction method based on spatial interpolation is proposed. The models use climate data from existing weather stations, digital elevation models surveys, and normalized difference vegetation index data to estimate a target site's next hour minimum temperature. The proposed method utilizes ensemble learning to increase the model accuracy. Ensemble methods include averaging and weighted averaging. Climate datasets are obtained from 75 weather stations across New South Wales and Australian Capital Territory areas of Australia. The models are constructed with five-fold validation, splitting the weather stations into five testing dataset folds. For each fold, the other stations act as training datasets. After the models are constructed, three experiments are conducted. The first experiment compares the results generated by models between different folds. Then, the second experiment compares the accuracy of different methods. The final experiment reveals the effect of available stations on the proposed models. The results show that the proposed method reached a detection rate up to 92.55%. This method could be implemented as an alternative solution when on-site historical datasets are scarce.

Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, 2019

The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health... more The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health, e-commerce, smart cities, supply chain management, smart cars, cyber-physical systems and a lot more. However, the data collected and processed by IoT systems especially the ones with centralized control are vulnerable to availability, integrity, and privacy threats. Hence, we present "PrivySharing," a blockchain-based innovative framework for integrity and privacy-preserving IoT data sharing in a smart city environment. The proposed scheme is distinct from existing technologies on many aspects. The data privacy is preserved by dividing the blockchain network into various channels, where every channel processes a specific type of data such as health, smart car, smart energy or financial data. Moreover, access to user data within a channel is controlled by embedding access control rules in the smart contracts. In addition, users' data within a channel is further isolated and secured by using private data collection. Likewise, the REST API that enables clients to interact with the blockchain network has dual security in the form of an API Key and OAuth 2.0. The proposed solution also conforms to some of the significant requirements outlined in the European Union General Data Protection Regulation. Lastly, we present a system of reward in the form of a digital token "PrivyCoin" for the users for sharing their data with the stakeholders/third parties.

2020 IEEE 45th Conference on Local Computer Networks (LCN), 2020

The existing lottery-based consensus algorithms, such as Proof-of-Work, and Proof-of-Stake, are m... more The existing lottery-based consensus algorithms, such as Proof-of-Work, and Proof-of-Stake, are mostly used for blockchain-based financial technology applications. Similarly, the Byzantine Fault Tolerance algorithms do provide consensus finality, yet they are either communications intensive, vulnerable to Denial-of-Service attacks, poorly scalable, or have a low faulty node tolerance level. Moreover, these algorithms are not designed for the Internet of Things systems that require near-real-time transaction confirmation, maximum fault tolerance, and appropriate transaction validation rules. Hence, we propose "Pledge," a unique Proof-of-Honesty based consensus protocol to reduce the possibility of malicious behavior during blockchain consensus. Pledge also introduces the Internet of Things centric transaction validation rules. Initial experimentation shows that Pledge is economical and secure with low communications complexity and low latency in transaction confirmation.

2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2020

Exhibition of malicious behavior during blockchain consensus, threats against reputation systems,... more Exhibition of malicious behavior during blockchain consensus, threats against reputation systems, and high TX latency are significant issues for blockchain-based IoT systems. Hence, to mitigate such challenges we propose "Pledge", a unique Proof-of-Honesty based consensus protocol. Initial experimentation shows that Pledge is economical with low computations and communications complexity and low latency in transaction confirmation.

IEEE Access

Applications and technologies of the Internet of Things are in high demand with the increase of n... more Applications and technologies of the Internet of Things are in high demand with the increase of network devices. With the development of technologies such as 5G, machine learning, edge computing, and Industry 4.0, the Internet of Things has evolved. This survey article discusses the evolution of the Internet of Things and presents the vision for Internet of Things 2.0. The Internet of Things 2.0 development is discussed across seven major fields. These fields are machine learning intelligence, mission critical communication, scalability, energy harvesting-based energy sustainability, interoperability, user friendly IoT, and security. Other than these major fields, the architectural development of the Internet of Things and major types of applications are also reviewed. Finally, this article ends with the vision and current limitations of the Internet of Things in future network environments.

IEEE Internet of Things Journal