Blockchain technology has been developed for more than ten years and has become a trend in various industries As the oil and gas industry is gradually shifting toward intelligence and digitalization, many large oil and gas companies were working on blockchain technology in the past two years because of it can significantly improve the management level, efficiency, and data security of the oil and gas industry This paper aims to let more people in the oil and gas industry understand the blockchain and lead more thinking about how to apply the blockchain technology To the best of our knowledge, this is one of the earliest papers on the review of the blockchain system in the oil and gas industry This paper first presents the relevant theories and core technologies of the blockchain, and then describes how the blockchain is applied to the oil and gas industry from four aspects: trading, management and decision making, supervision, and cyber security Finally, the application status, the understanding level of the blockchain in the oil and gas industry, opportunities, challenges, and risks and development trends are analyzed The main conclusions are as follows: 1) at present, Europe and Asia have the fastest pace of developing the application of blockchain in the oil and gas industry, but there are still few oil and gas blockchain projects in operation or testing worldwide; 2) nowadays, the understanding of blockchain in the oil and gas industry is not sufficiently enough, the application is still in the experimental stage, and the investment is not enough; and (3) blockchain can bring many opportunities to the oil and gas industry, such as reducing transaction costs and improving transparency and efficiency However, since it is still in the early stage of the application, there are still many challenges, primarily technological, and regulatory and system transformation The development of blockchains in the oil and gas industry will move toward hybrid blockchain architecture, multi-technology combination, cross-chain, hybrid consensus mechanisms, and more interdisciplinary professionals

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Blockchain Technology in the Oil and Gas Industry: A Review of Applications, Opportunities, Challenges, and Risks

The growing demand for human-independent comfortable lifestyle has emboldened the development of smart home. A typical keenly intellective home includes many Internet of things contrivances that en...

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SH-BlockCC: A secure and efficient Internet of things smart home architecture based on cloud computing and blockchain technology:

In the Internet-of-Things (IoT) era, user authentication is essential to ensure the security of connected devices and the customization of passive services However, conventional knowledge-based and physiological biometric-based authentication systems (eg, password, face recognition, and fingerprints) are susceptible to shoulder surfing attacks, smudge attacks, and heat attacks The powerful sensing capabilities of IoT devices, including smartphones, wearables, robots, and autonomous vehicles enable continuous authentication (CA) based on behavioral biometrics The artificial intelligence (AI) approaches hold significant promise in sifting through large volumes of heterogeneous biometrics data to offer unprecedented user authentication and user identification capabilities In this survey article, we outline the nature of CA in IoT applications, highlight the key behavioral signals, and summarize the extant solutions from an AI perspective Based on our systematic and comprehensive analysis, we discuss the challenges and promising future directions to guide the next generation of AI-based CA research

Behavioral Biometrics for Continuous Authentication in the Internet-of-Things Era: An Artificial Intelligence Perspective

Cyber-physical systems (CPS) is a setup that controls and monitors the physical world around us. The advancement of these systems needs to incorporate an unequivocal spotlight on making these systems efficient. Blockchains and their inherent combination of consensus algorithms, distributed data storage, and secure protocols can be utilized to build robustness and reliability in these systems. Blockchain is the underlying technology behind bitcoins and it provides a decentralized framework to validate transactions and ensure that they cannot be modified. By distributing the role of information validation across the network peers, blockchain eliminates the risks associated with a centralized architecture. It is the most secure validation mechanism that is efficient and enables the provision of financial services, thereby giving users more freedom and power. This upcoming technology provides internet users with the capability to create value and authenticate digital information. It has the capability to revolutionize a diverse set of business applications, ranging from sharing economy to data management and prediction markets. In this paper, we present a holistic survey of various applications of CPS where blockchain has been utilized. Smart grids, health-care systems, and industrial production processes are some of the many applications that can benefit from the blockchain technology and will be discussed in the paper.

https://www.mdpi.com/1424-8220/20/1/282/pdf

A Survey of Blockchain Enabled Cyber-Physical Systems

Tucker decomposition has been widely used to extract meaningful and underlying data from heterogeneous data generated by different kinds of devices in a wide range of industrial Internet of Things (IIoT) applications. IIoT data uploaded to the cloud contain personal and sensitive information; thus, there is a growing concern about data privacy. Current existing data analysis solutions, however, assume that the data are reliably and securely collected from different IIoT data providers, an assumption that is not always true in the real world. To address the issues, in this article we propose a privacy-preserving tucker train decomposition based on gradient descent over blockchain-based encrypted IIoT data. Specifically, we use blockchain techniques to enable IIoT data providers to reliably and securely share their data by encrypting them locally before recording them in the blockchain. We use tensor train (TT) theory to build an efficient TT-based tucker decomposition based on gradient descent that tremendously reduces the number of elements to be updated during the tucker decomposition. We utilize the massive resources of fogs and clouds to implement an efficient privacy-preserving tucker train decomposition scheme. We use homomorphic encryption to build our scheme that does complete tucker train decomposition without the involvement of users. Results from a series of extensive experiments on synthetic datasets and real-world datasets demonstrate that our proposed scheme is efficient.

Privacy-Preserving Tucker Train Decomposition Over Blockchain-Based Encrypted Industrial IoT Data

Blockchain as a new technique has attracted attentions from industry and academics for sharing data across organizations. Many blockchain-based data sharing applications, such as Internet of Things...

https://journals.sagepub.com/doi/pdf/10.1177/1550147718808750

A privacy-preserving Internet of Things device management scheme based on blockchain:

The increasing penetration of renewable and distributed resources signals a global boom in energy transition, but traditional grid utilities have yet to share in much of the triumph at the current stage. Higher grid management costs, lower electricity prices, fewer customers, and other challenges have emerged along the path toward renewable energy, but many more opportunities await to be seized. Most importantly, there are insufficient studies on how grid utilities can thrive within the hydrogen economy. Through a case study on the State Grid Corporation of China, we identify the strengths, weaknesses, opportunities, and threats (SWOT) of grid utilities within the hydrogen economy. Based on these factors, we recommend that grids integrate hydrogen into the energy-as-a-service model and deliver it to industrial customers who are under decarbonization pressure. We also recommend that grid utilities fund a joint venture with pipeline companies to optimize electricity and hydrogen transmissions simultaneously.

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How a Grid Company Could Enter the Hydrogen Industry through a New Business Model: A Case Study in China

Hydrogen is crucial in achieving global energy transition and carbon neutrality goals. Existing market estimates typically presume linear or exponential growth but fail to consider how market demand responds to the declining cost of underlying technologies. To address this, this study utilizes a learning curve model to project the cost of electrolyzers and its subsequent impact on hydrogen market, aligning with a premise that the market demand is proportional to the cost of hydrogen. In a case study of China’s hydrogen market, projecting from 2020 to 2060, we observed substantial differences in market evolution compared to exponential growth scenarios. Contrary to exponential growth scenarios, China’s hydrogen market experiences faster growth during the 2020–2040 period rather than later. Such differences underscore the necessity for proactive strategic planning in emerging technology markets, particularly for those experiencing rapid cost decline, such as hydrogen. The framework can also be extended to other markets by using local data, providing valuable insights to investors, policymakers, and developers engaged in the hydrogen market.

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Linking Cost Decline and Demand Surge in the Hydrogen Market: A Case Study in China

Hydrogen production from electrolytic water can realize the absorption of new energy, and hydrogen production from new energy electricity has no direct carbon emissions, but the electricity production process will produce different degrees of indirect carbon emissions to hydrogen production from electrolytic water according to different power generation sources. Therefore, this paper takes the carbon price into account in the cost of hydrogen production from electric water, and analyzes the levelized cost of hydrogen production from electrolytic water under different power sources, It is concluded that the total cost of hydrogen production in the low valley electricity electrolysis water hydrogen production process is most sensitive to the carbon price, and the cost of hydrogen production under each power source increases with the carbon price, and gradually slows down.

Economic Analysis of Hydrogen Production from Electrolytic Water Considering Carbon Emissions

Traditionally, transactions on the Internet need to be handled by trusted third-party credit agencies. As a new technology for the encrypted transmission of transaction information, blockchain technology is based on the principle of cryptography, so that it does not require the participation of third parties. Blockchain technology can be widely used in many fields, such as the power industry. On the one hand, blockchain technology can greatly reduce the system cost in electricity trading because it can be independent of the central organization and ensure the authenticity and non-tampering of data. On the other hand, in electricity trading, the user’s personal information and transaction information need to be encrypted and protected, and a fine-grained access control scheme is provided to ensure the security of the transactions. In our paper, we propose a privacy-preserving electricity trading scheme which applies blockchain technology to electricity trading and combined with the decentralized policy-hiding attribute-based encryption scheme to achieve fine-grained access control and protect users’ private information.

Zhoubin Liu

Papers

A privacy-preserving Internet of Things device management scheme based on blockchain:

How a Grid Company Could Enter the Hydrogen Industry through a New Business Model: A Case Study in China

Linking Cost Decline and Demand Surge in the Hydrogen Market: A Case Study in China

Economic Analysis of Hydrogen Production from Electrolytic Water Considering Carbon Emissions

A Privacy-Preserving Electricity Trading Scheme Based on Blockchain