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We like and need Information and Communication Technologies (ICTs) for data processing. This is measurable in the exponential growth of data processed by ICT, e.g., ICT for cryptocurrency mining and search engines. So far, the energy demand for computing technology has increased by a factor of 1.38 every 10 years due to the exponentially increasing use of ICT systems as computing devices. Energy consumption of ICT systems is expected to rise from 1500 TWh (8% of global electricity consumption) in 2010 to 5700 TWh (14% of global electricity consumption) in 2030 [A. S. G. Andrae, Eng. Appl. Sci. Lett. 3, 19–31 (2020)]. A large part of this energy is required for the continuous data transfer between separated memory and processor units, which constitute the main components of ICT computing devices in von-Neumann architecture. This, at the same time, massively slows down the computing power of ICT systems in von-Neumann architecture. In addition, due to the increasing complexity of artificial intelligence (AI) compute algorithms, since 2010, the AI training compute time demand for computing technology has increased tenfold every year, for example, from 1 × 10−6 to 1 × 10+4 Petaflops/day in the period from 2010 to 2020 [J. Wang, see https://ark-invest.com/articles/analyst-research/ai-training/ for information about the cost to train an AI interference system (2020)]. It has been theoretically predicted that ICT systems in the neuromorphic computer architecture will circumvent all of this through the use of merged memory and processor units. However, the core hardware element for this has not yet been realized so far. In this work, we discuss the perspectives for non-volatile resistive switches with hysteretic memristance as the core hardware element for merged memory and processor units in neuromorphic computers. [ABSTRACT FROM AUTHOR]

The environmental impact of Bitcoin mining has raised severe concerns considering the expected growth of 30% by 2030. This study aimed to develop a Life Cycle Assessment model to determine the carbon dioxide equivalent emissions associated with Bitcoin mining, considering material requirements and energy demand. By applying the impact assessment method IPCC 2021 GWP (100 years), the GHG emissions associated with electricity consumption were estimated at 51.7 Mt CO2 eq/year in 2022 and calculated by modelling real national mixes referring to the geographical area where mining takes place, allowing for the determination of the environmental impacts in a site-specific way. The estimated impacts were then adjusted to future energy projections (2030 and 2050), by modelling electricity mixes coherently with the spatial distribution of mining activities, the related national targeted goals, the increasing demand for electricity for hashrate and the capability of the systems to recover the heat generated in the mining phase. Further projections for 2030, based on two extrapolated energy consumption models, were also determined. The outcomes reveal that, in relation to the considered scenarios and their associated assumptions, breakeven points where the increase in energy consumption associated with mining nullifies the increase in the renewable energy share within the energy mix exist. The amount of amine-based sorbents hypothetically needed to capture the total CO2 equivalent emitted directly and indirectly for Bitcoin mining reaches up to almost 12 Bt. Further developments of the present work would rely on more reliable data related to future energy projections and the geographical distribution of miners, as well as an extension of the environmental categories analyzed. The Life Cycle Assessment methodology represents a valid tool to support policies and decision makers. [ABSTRACT FROM AUTHOR]

This article primally explores the short-term fluctuation and long-term implications of the international Bitcoin price (BP) on the Chinese green bond (GB) market, within the sample period of 2014:M10-2023:M07. Bitcoin is the most important cryptocurrency and has a carbon-intensive feature, and its price suffers from great volatility and is closely related to the green finance market. Meanwhile, although China is the largest bitcoin mining state, it is pursuing a dual carbon target, which promotes its green bond market's development. Thus, it is valuable to investigate the influence of BP on GBs in China. Based on the quantile autoregressive distributed lag approach, this paper indicates that the positive and negative impacts of BP on the GB market are significant in the long-term but not apparent in the short-term. These results emphasize the importance for market participants to obtain a better understanding of how BP affects GB under various market circumstances. Implementing specific policies, such as regulatory mechanisms for Bitcoin trade, market-oriented reform for the bond market, and information disclosure, can alleviate shocks from BP and accelerate the development of the GB market. [ABSTRACT FROM AUTHOR]

In January 2022, a massive power blackout hit Central Asia, and especially the southern region of Kazakhstan after months of a huge rise in electricity consumption in the country and a few days after deadly demonstrations repressed by law enforcement. According to the Kazakhstani authorities, this huge power outage was due to cryptocurrency mining, an energy-intensive digital industry, highly developed within the country. This article aims to analyse and understand the geopolitical dynamics behind the fast and huge-scale development of the activity in Kazakhstan. The paper explores the geography of mining to and within the country, and relates it to the double territory's divide, both climatic and energetic. Then, it analyses the political aspect of mining focusing on actors and networks of power involved in, sometimes illegal, crypto mining in Kazakhstan. Finally, this work discusses the future of the industry regarding the new regulation since 2023 and its limits. [ABSTRACT FROM AUTHOR]

We develop a theory of blockchain governance. In our model, the proof-of-work system , the most common set of rules for validating transactions in blockchains, creates an industrial ecosystem with specialized suppliers of goods and services. We analyze the interactions between blockchain governance and the market structure of the industries in the blockchain ecosystem. We show that the proof-of-work system may lead to a situation in which some large firms in the blockchain industrial ecosystem— blockchain conglomerates —capture the governance of the blockchain. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

The continuous and round-the-clock operation of cryptocurrency mining devices generates significant heat that requires powerful cooling systems. Therefore, the main problem of mining is its high electricity consumption and energy usage. Unfortunately, due to the lack of planning by the country's officials, we are facing the problem of electricity shortage, which the growing digital currencies have exacerbated. Since decision-making in the real world (including the electricity shortage problem caused by mining) is complex and uncertain due to various influential factors, this research aims to apply a strategic selection approach to decision-making and provide solutions to solve the electricity shortage problem caused by cryptocurrency mining in Iran. In this study, the Strategic Choice Approach (SCA), one of the soft operational research methods, has been used for analysis, structuring, and decision tree development. For this purpose, four methods (styles) of SCA, which include ten steps, have been implemented. A working group consisting of twelve experts and stakeholders in digital currencies, facilitated by the researchers of this study, has been formed, and specific flowcharts and labels have been used. According to the SCA method, decision-making areas, decision options, areas of uncertainty, exploratory options, and decision trees have been designed. Finally, a ″commitment package″ (″improvement package″) has been proposed to provide practical solutions. This article provides solutions for solving the electricity shortage problem caused by cryptocurrency mining through the SCA. For this purpose, specific tasks have been assigned to the Islamic Consultative Assembly, the Ministry of Economy, the Ministry of Energy and Foreign Affairs, and the government, excluding the mentioned ministries and some key players in digital currencies, which should be carried out in the present and future. By structuring the research problem through the SCA method as one of the soft operations research methods, the readers and users of this research will learn more details and dimensions of the mentioned method, contributing to expanding their knowledge of soft operations research. Although the SCA method has been implemented in Iran and other countries for a long time in various social and organizational issues, the diagrams, shapes, and tables used to implement SCA in this research contribute more to the readers' knowledge. It also helps to localize this method and other research done in the country.

In parallel with the growing interest in cryptocurrencies, the relationship between crypto trading and CO2 is critical to drive financial markets and environmental sustainability efforts. The aim of this study is to analyse the impact of crypto trading on carbon emissions (CO2) through the mediating roles of international trade and energy use. Within the scope of the study, path analysis was carried out using the 2007-2021 period data of the top 20 countries with high crypto trade volume. A model proposal was presented to examine the relationships between the variables used in the study and the necessary analyses were carried out. The results of the analysis show that crypto trade volume has a positive and significant effect on carbon emissions. It is also concluded that international trade and energy use mediate the relationship between crypto trade and carbon emissions. It is seen that crypto mining activities and cryptocurrencies lead to an increase in energy use and environmental impacts. At this point, it is important for countries to switch to renewable energy sources and to regularly report and monitor the impact of cryptocurrency mining activities on carbon emissions. [ABSTRACT FROM AUTHOR]

Cryptocurrencies are quickly becoming a key tool in investment decisions. The volatile nature of bitcoin prices has spurred the demand for robust predictive models. The primary objective of this study is to evaluate and compare the effectiveness of different machine learning models with the combination of technical indicators in predicting bitcoin prices. The study used 27 critical technical indicators to evaluate four machine learning techniques, namely Artificial Neural Network (ANN), a Hybrid Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM), Support Vector Machine (SVM), and Random Forest. The results showed that ANN and SVM achieve a significant prediction accuracy of 81% and 82%, respectively, which is higher than the results of traditional models such as standard ARIMA. In practical applications, these methods often improve prediction accuracy by 20-30% over traditional models. The novelty of the analysis lies in the use of temporal and spatial trends via momentum, ROC, and %K features, making for a holistic approach to cryptocurrency market forecasting. This study underscores the critical importance of specific technical indicators and the imperative role of data mining in revolutionizing cryptocurrency market navigation. The research results highlight opportunities to improve investment strategies and risk management policies in the bitcoin market using machine learning models, making the latter valuable to investors and financial experts. [ABSTRACT FROM AUTHOR]

The article provides an overview of the history of cryptocurrency and the current taxation and regulatory framework for cryptocurrencies. It discusses the conflicting views of the SEC and the IRS on whether cryptocurrencies should be classified as securities or property. The article highlights the challenges and shortcomings of current tax policies regarding cryptocurrencies, including the lack of specialized tax rules and the inapplicability of certain provisions. It suggests that the IRS should create a new classification for cryptocurrencies and update its tax system to effectively tax them. However, due to the unique nature of cryptocurrencies, there may never be a perfect solution. [Extracted from the article]

Crypto-jacking attack is a novel type of cyber-attack on the internet that has emerged because of the popularity of digital currencies. These attacks are the most common type of attacks in the cryptocurrency field because of their specific features such as easy scenario, un-traceability, and ease of secrecy. In crypto-jacking attacks, it is common to embed malicious code inside website scripts. Different techniques have been provided to deal with Crypto-jacking attacks, but crypto-jacking attackers bypass them by limiting resources. The crypto-mining services provided on the internet are legal, and due to the anonymous nature of cryptocurrencies, client identification is a challenging task. Improving the accuracy and performance of the Crypto-jacking attack detection methods are the main objectives of this study. In this paper, a hybrid network-based method to identify these attacks to achieve better and more accurate results. The proposed solution (CMShark) is a combination of machine learning (ML) models, IP blacklisting and payload inspection methods. In the ML model, the packets are classified using size patterns; in IP blacklisting, attacks are detected based on known infected addresses and infected scripts. In payload inspection, the provided information on the packet payload is searched for any suspicious keywords. The proposed method relies solely on the network and is deployed on the edge of the network, making it infrastructureindependent. The proposed detection model reaches an accuracy score of 97.02%, an F1-score of 96.90% a ROC AUC score of 97.20% in input NetFlow classification; and a 93.98% accuracy score, 94.30% F1-score and 97.30% ROC AUC score in output NetFlow classification. [ABSTRACT FROM AUTHOR]

The continuous and round-the-clock operation of cryptocurrency mining devices generates significant heat that requires powerful cooling systems. Therefore, the main problem of mining is its high electricity consumption and energy usage. Unfortunately, due to the lack of planning by the country's officials, we are facing the problem of electricity shortage, which the growing digital currencies have exacerbated. Since decision-making in the real world (including the electricity shortage problem caused by mining) is complex and uncertain due to various influential factors, this research aims to apply a strategic selection approach to decision-making and provide solutions to solve the electricity shortage problem caused by cryptocurrency mining in Iran. In this study, the Strategic Choice Approach (SCA), one of the soft operational research methods, has been used for analysis, structuring, and decision tree development. For this purpose, four methods (styles) of SCA, which include ten steps, have been implemented. A working group consisting of twelve experts and stakeholders in digital currencies, facilitated by the researchers of this study, has been formed, and specific flowcharts and labels have been used. According to the SCA method, decision-making areas, decision options, areas of uncertainty, exploratory options, and decision trees have been designed. Finally, a "commitment package" ("improvement package") has been proposed to provide practical solutions. This article provides solutions for solving the electricity shortage problem caused by cryptocurrency mining through the SCA. For this purpose, specific tasks have been assigned to the Islamic Consultative Assembly, the Ministry of Economy, the Ministry of Energy and Foreign Affairs, and the government, excluding the mentioned ministries and some key players in digital currencies, which should be carried out in the present and future. By structuring the research problem through the SCA method as one of the soft operations research methods, the readers and users of this research will learn more details and dimensions of the mentioned method, contributing to expanding their knowledge of soft operations research. Although the SCA method has been implemented in Iran and other countries for a long time in various social and organizational issues, the diagrams, shapes, and tables used to implement SCA in this research contribute more to the readers' knowledge. It also helps to localize this method and other research done in the country. [ABSTRACT FROM AUTHOR]

Newly emerged events in the world of technology call on jurisconsults to make extra efforts to align them with jurisprudential institutions and dos-and-don'ts and to try to regulate them. One of these technologies is the mining of cryptocurrencies. The present study analyzes the jurisprudential nature of cryptocurrency, using the descriptive-analytical method, in order to determine the ruling on cryptocurrency mining. It is concluded that cryptocurrency mining does not align with the hire contract in terms of the manner of offer (ījāb) and the conditions of contracting parties. It is also different in subject matter from the possession of ownerless profaty (ḥiyāzat-i mubāḥāt). This occures optional or non-optional while cryptocurrency mining is not. In other words, it is not the case that a number of cryptocurrencies exist for a fason to extract using some tools, which would be considered as mining. Rather, the fason is given a certain amount of cryptocurrency in exchange for the work they have done. Cryptocurrency mining is also different from the contract of gift (Hibbah), in terms of conditions of the offeror (mujib), the acceptor (qābil), and the act of taking possession (qabż). In the end, cryptocurrency mining can be aligned with the contract of Jiʿālah ʿām. However, even in this case, considering cryptocurrency as Jiʿālah does not legitimize the act. There are several other issues such as the lack of value, the incompetent trades of mining (the state of being Safahī), etc., which may be analyzed in future research. [ABSTRACT FROM AUTHOR]

The carbon footprint generated by the information and communications technology (ICT) sector is increasingly significant, emitting greenhouse gases due to high energy consumption, regardless of the way in which energy is generated, the expansion and growth in data centers, as well as the impact generated by the cryptocurrency sector that in the end represents is reflected in greater consumerism, processing, storage, and transport of information that will be somewhere in the world. Current research addresses the problems and the contrast of figures in energy consumption due to the use of a computer, data processing, the role of the user as an internet consumer, the impact of data centers both in carbon footprint, water footprint and soil footprint, the impact of cryptocurrency mining and its contribution to global energy expenditure as well as the ethical debate of new technologies. And finally, the advances in seeking to optimize energy resources, sustainable and conscious for both consumers and service providers, show the trends focused on energy optimization through software and hardware based on a judicious review of research documents. [ABSTRACT FROM AUTHOR]

The cryptocurrency mining sector in Kazakhstan has witnessed remarkable expansion, attracting global miners due to favourable conditions. However, this growth has underscored the country’s energy scarcity, leading to the enforcement of stringent regulations by the government. This article seeks to offer a thorough comprehension of the regulatory framework governing cryptocurrency mining in Kazakhstan. Examining diverse aspects such as the legal status of mining, licensing structures, tax considerations, and the impact on energy infrastructure, the study utilizes international experiences and stimulus materials. Through the analysis of media representation and examination of primary trends, it is revealed that while the government has addressed legal gaps and instituted transparent tax procedures, taxing digital mining may discourage foreign investments, given the industry’s current fragility due to excessive regulations. The article provides insights into the regulatory landscape, emphasizing challenges and opportunities.

The annual electricity consumption of cryptocurrency mining has witnessed significant growth in recent years, fueled by an increase in market participation and the escalating complexity of the mining process. This has led to carbon emissions that exceed those generated by several developed nations. The growing impact of global warming and rising environmental concerns has brought increased scrutiny to Bitcoin’s energy consumption, particularly its potential to influence prices in unforeseen ways. This study investigates multifractal behavior in the cross-correlation of the Cambridge Bitcoin Electricity Consumption Index (CBECI) with both conventional and renewable energy prices using the Multifractal Detrended Cross-Correlation Analysis (MFDCCA) method. For renewable energy, we considered WilderHill Clean Energy, S&P Global Eco, S&P Global Clean Energy, OMX Solar Energy, and OMX Renewable Energy Index. For conventional energy, we considered the daily prices of WTI crude oil, Brent oil, heating oil, Newcastle coal, and natural gas. The daily price data range from 2 April 2013, to 29 August 2023, encompassing 1709 observations. Additionally, we employed a rolling window analysis to uncover the time-varying dynamics in the cross-correlations and persistence levels between Bitcoin electricity consumption and energy prices. The findings reveal the existence of a cross-correlation between the CBECI and energy markets. Overall, the CBECI exhibits a persistent cross-correlation with both energy markets; however, it is more persistent in the fossil fuel market, specifically in the coal market. These findings suggest the incorporation of dynamic changes in the CBECI in portfolio management for effective risk management strategies.

Climate change persists as a pressing global issue due to high greenhouse gas emissions from fossil fuel-based energy sources. A transition to a greener energy matrix combined with carbon offsetting is imperative to mitigate the rate at which global temperature ascends. While countries have deployed faith in green hydrogen to accelerate worldwide decarbonization efforts, the concurrent rise of blockchain-operated crypto-applications, such as bitcoin, has exacerbated climate change concerns. In this study, we propose technological solutions that combine the green hydrogen infrastructure with bitcoin mining operations to catalyze environmental and socioeconomic sustainability in climate change mitigation strategies. Since the present state of crypto-operations undeniably contributes to worldwide carbon emissions, it becomes vital to explore opportunities for harnessing the widespread enthusiasm for bitcoin as an aid toward a sustainable and climate-friendly future. Our findings reveal that green hydrogen production, paired with crypto-operations, can accelerate the deployment of solar and wind power capacities to boost conventional mitigation frameworks. Specifically, leveraging the economic potential derived from green hydrogen and bitcoin for incremental investment in renewable energy penetration, this dynamic duo can enable capacity expansions of up to 25.5% and 73.2% for solar and wind power installations. Therefore, the proposed technological solutions that leverage green hydrogen and bitcoin mining, bolstered with appropriate policy interventions, can not only strengthen renewable power generation and carbon offsetting capacities but also contribute significantly to achieving climate sustainability. [ABSTRACT FROM AUTHOR]

As the value of bitcoin soars to record levels, the environmental impacts of cryptocurrency mining are attracting scrutiny from governments. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this research is to analyze the relationship among cryptocurrency mining, economic growth and unemployment rate with various other determinants by utilizing panel data from 2015 to 2023, while focusing on 10 crypto-trader countries: Canada, China, Germany, Iceland, Iran, Kazakhstan, Malaysia, Russia, United States, and Singapore. Data is sourced from World Development Indicators (WDI) and cryptocurrency-specific websites. Design/Methodology/Approach: By employing econometrical research techniques such as System GMM, the research analyzes two key models to understand the relationship among cryptocurrency mining, economic growth & unemployment rate. Findings: Model-A explores the relationship among GDP per capita growth (proxy for economic growth) and cryptocurrency mining including various other determinants, and observed positive relationships while CO2 exhibits a negative coefficient. Model-B explores the relationship among unemployment rate and cryptocurrency mining including various other determinants, and observed negative relationships while government expenditure on education and secondary school education exhibits a positive relationship. Implications/Originality/Value: The research study contributes to the prevailing literature by providing empirical evidence and insights into the macroeconomic implications of cryptocurrency mining activities, offering valuable contemplations for policymakers, economists, and stakeholders in navigating the evolving landscape of cryptocurrency and its impacts on economic growth and labor markets. [ABSTRACT FROM AUTHOR]

Advertising has been the most common strategy for content monetization. However, behavioral data collection for personalized advertisements has raised privacy concerns. This study explores users' perceptions of browser-based cryptocurrency mining (BCM) as an alternative content monetization method to online advertising. The mining process is an essential part of blockchain technology, but it is a resource-intensive process. By utilizing BCM, content providers can mine cryptocurrency on the computers of website visitors and provide free or discounted services for the cost of the mining process. Considering that BCM revenue can be comparable to online advertisement while preserving user privacy at a negligible cost, we explored underlying factors affecting the adoption of BCM. We conducted a qualitative exploratory study using linguistic analysis and topic modeling of data collected from an online focus group. The results revealed that users raised security concerns and resisted BCM adoption due to its negative image and potential risk barriers. Our results further showed that online advertising benefits from the status quo bias. That is, although users raised both privacy and security concerns, they still considered online advertising. We extend the literature by analyzing controversial technology in the light of incumbent technology and provide directions for implementing BCM as a successful revenue stream. [ABSTRACT FROM AUTHOR]

We propose a mean field game model to study the question of how centralization of reward and computational power occur in Bitcoin-like cryptocurrencies. Miners compete against each other for mining rewards by increasing their computational power. This leads to a novel mean field game of jump intensity control, which we solve explicitly for miners maximizing exponential utility and handle numerically in the case of miners with power utilities. We show that the heterogeneity of their initial wealth distribution leads to greater imbalance of the reward distribution, and increased wealth heterogeneity over time, or a "rich get richer" effect. This concentration phenomenon is aggravated by a higher Bitcoin mining reward and reduced by competition. Additionally, an advantaged miner with cost advantages such as access to cheaper electricity, contributes a significant amount of computational power in equilibrium, unaffected by competition from less efficient miners. Hence, cost efficiency can also result in the type of centralization seen among miners of cryptocurrencies. This paper was accepted by Kay Giesecke, finance. Funding: A. M. Reppen is partly supported by the Swiss National Science Foundation [Grant SNF 181815]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4798. [ABSTRACT FROM AUTHOR]

Blockchain technology is a decentralized and secure paradigm for data processing, sharing, and storing. It relies on consensus protocol for all decisions, which focuses on computational and resource capability. For example, proof of work (PoW) and proof of stake (PoS) are the most famous consensus protocols that are currently used. However, these current consensus protocols are required to recruit a node with a high computational or a large amount of cryptocurrency to act as a miner node and to generate a new block. Unfortunately, these PoW and PoS protocols could be impractical for adoption in today's technological fields, such as the Internet of Things and healthcare. In addition, these protocols are susceptible to flexibility, security, and fairness issues, as they are discussed in detail in this work. Therefore, this paper introduces a proof of fairness (PoF) as a dynamic and secure consensus protocol for enhancing the mining selection process. The selection of the miner node is influenced by numerous factors, including the time required to generate a block based on the transaction's sensitivity. Firstly, a reverse auction mechanism is designed as an incentive mechanism to encourage all nodes to participate in the miner selection process. In a reverse auction, each node will draw its strategy based on its computational capability and claimed cost. Secondly, an expressive language is developed to categorize transaction types based on their sensitivity to processing time, ensuring compatibility with our miner selection process. Thirdly, a homomorphic concept is designed as a security and privacy scheme to protect the bidder's data confidentiality. Finally, an extensive evaluation involving numerical analysis was carried out to assess the efficiency of the suggested PoF protocol, which confirms that the proposed PoF is dynamic and more efficient than current PoW and PoS consensus protocols. [ABSTRACT FROM AUTHOR]

Cryptocurrencies, such as Bitcoin (BTC), based on the proof-of-work mining production scheme create significant social costs. This analysis monetarily estimates the health and climate damages of BTC mining in the United States (US) from September 2019 to December 2021, and then compares these damages to BTC's market price. We further show the spatial dispersion of BTC's 'social damage-to-market price' ratio across US states. If this benchmark ratio is >1, then it is a clear indicator of an unsustainable technology. Results indicate significant geographic hotspots and periods when BTC mining generates social costs that exceed the market price—i.e. instances where BTC is underwater. On average, for the US, damages represented 49% of the value of the coins generated and BTC was underwater on approximately one-quarter of days between September 2019 and December 2021. Several US states have average damages that exceed the value of each BTC mined. [ABSTRACT FROM AUTHOR]

WebAssembly is a low-level bytecode language that enables high-level languages like C, C++, and Rust to be executed in the browser at near-native performance. In recent years, WebAssembly has gained widespread adoption and is now natively supported by all modern browsers. Despite its benefits, WebAssembly has introduced significant security challenges, primarily due to vulnerabilities inherited from memory-unsafe source languages. Moreover, the use of WebAssembly extends beyond traditional web applications to smart contracts on blockchain platforms, where vulnerabilities have led to significant financial losses. WebAssembly has also been used for malicious purposes, like cryptojacking, where website visitors' hardware resources are used for crypto mining without their consent. To address these issues, several analysis techniques for WebAssembly binaries have been proposed. This paper presents a systematic review of these analysis techniques, focusing on vulnerability analysis, cryptojacking detection, and smart contract security. The analysis techniques are categorized into static, dynamic, and hybrid methods, evaluating their strengths and weaknesses based on quantitative data. Our findings reveal that static techniques are efficient but may struggle with complex binaries, while dynamic techniques offer better detection at the cost of increased overhead. Hybrid approaches, which merge the strengths of static and dynamic methods, are not extensively used in the literature and emerge as a promising direction for future research. Lastly, this paper identifies potential future research directions based on the state of the current literature. [ABSTRACT FROM AUTHOR]

Renewable electrical energy (such as: solar and wind energies) generation in microgrids (MGs), is gaining attention to reduce greenhouse gas emissions. Microgrid operators (MOs) aim to create self-sufficient, environmentally sustainable grids, increasing the capacity of renewable energy sources (RESs) by up to 100%. Despite of the benefits of this trend, challenges arise from non-controlled characteristics of these power generations and their seasonal variations, causing fluctuations and renewable energy curtailment. Although the technical solutions; such as: the demand response (DR) programs, and the conventional electrical energy storage systems (EESSs) can help, however those may face limitations in countries with high seasonal energy generation and consumption variations. This paper introduces cryptocurrency mining loads (CMLs) as innovative virtual energy storage systems (VESSs), named cryptocurrency energy storage systems (CESSs). It proposes a structure to store excess renewable energy in cryptocurrency units (CCUs) like Bitcoin (BTC). CESSs can be charged during off-peak intervals and, conversely, they discharge during high-demand periods to reduce the overall operational cost of MGs. Furthermore, it presents a new energy management system (EMS) formulation for the optimal operation of MGs in the presence of CESSs, providing an opportunity to generate additional electricity from RESs and to mitigate renewable energy curtailment. This paper explores the optimal operation conditions of both islanded and grid-connected MG with the proposed CESS. Utilizing a dataset from an island in Finland as a practical MG, its effectiveness is demonstrated through several case studies. The results of one case study in this paper demonstrate that the proposed CESS can decrease the operating cost of the MG by about 46.5%. Additionally, it is showed that by application of CESS the renewable energy curtailment is significantly reduced, and approached zero.

‌ ∴ Introduction ∴ ‌ In the rapidly evolving landscape of digital technology, the emergence of blockchain and cryptocurrencies has presented new challenges and questions for religious jurisprudence. Among these, the practice of cryptocurrency mining has sparked debates concerning its conformity with Islamic laws, particularly in light of similarities drawn between mining activities and gambling [Ghomar] — a concept well-defined and often condemned in Islamic teachings. This paper aims to explore the intricate dynamics of cryptocurrency mining within the framework of Imamia Jurisprudence, scrutinizing whether the practice bears the hallmarks of gambling, as traditionally understood within the Sharia. Given the profound impact of digital currencies on global financial systems and the ethical considerations they raise, this investigation seeks to elucidate the religious standings on cryptocurrency mining, thereby guiding adherents in their engagement with this modern financial phenomenon. ‌ ∴ Research Question ∴ ‌ The core inquiry of this study revolves around the assessment of cryptocurrency mining through the lens of Imamia Jurisprudence: "Does the process of cryptocurrency mining align with the characteristics of gambling as defined by Islamic law, thereby rendering it prohibited. This question seeks to unravel the ethical and religious implications of mining activities, which involve significant financial investment in competition for a potentially lucrative reward, mirroring aspects of chance and speculation akin to gambling. ‌ ∴ Research Hypothesis ∴ ‌ This paper hypothesizes that despite superficial similarities between cryptocurrency mining and gambling—such as the reliance on chance, competitive investment, and the potential for monetary gain without traditional labor—there are fundamental differences that could distinguish mining activities from gambling under Imamia Jurisprudence. These differences hinge on the intentions behind mining, the nature of effort and investment involved, and the broader economic implications of cryptocurrency within Islamic ethical frameworks. The hypothesis posits that a nuanced understanding of these factors may reveal that cryptocurrency mining does not inherently constitute gambling and thus may not be universally deemed haram within an Islamic context. ‌ ∴ Methodology & Framework, if Applicable ∴ ‌ To address the research question and test the hypothesis, this study adopts a descriptive analytical methodology, underpinned by a qualitative framework that involves the examination of primary and secondary sources within Islamic jurisprudence. The research will delve into the canonical texts, fatwas, and scholarly interpretations that define gambling from an Imamia perspective, subsequently applying these criteria to the process of cryptocurrency mining. Through comparative analysis, the study will identify the parallels and distinctions between mining and gambling, considering factors such as the element of risk, the role of skill versus chance, and the societal and economic contributions of cryptocurrency mining. This methodological approach allows for a comprehensive assessment of the subject matter, grounded in the rich tradition of Islamic legal scholarship while engaging with the contemporary implications of digital finance. ‌ ∴ Results & Discussion ∴ ‌ The research meticulously dissected the characteristics traditionally associated with gambling within Islamic jurisprudence and juxtaposed these with the intrinsic elements of cryptocurrency mining. This comparative analysis yielded several critical insights, underscoring the distinct nature of cryptocurrency mining from gambling. Key findings include: Rational benefit and ecosystem contribution: cryptocurrency mining was found to offer tangible benefits to the digital currency ecosystem, enhancing security and facilitating transactions. This utility and contribution render it distinct from gambling activities, which lack productive output or societal benefit. Nature of rewards: unlike gambling, where stakes are placed with the possibility of total loss or gain based on chance, cryptocurrency mining rewards are not predicated on the loss of another but are rewards for computational efforts contributed to the network. Financial risk and effort: the research clarified that the financial investment in mining does not equate to wagering since it involves expenditure towards productive work with inherent value, differentiating it from the speculative risk in gambling. Competition and intent: the competitive aspect of mining does not inherently signify gambling, as it lacks the direct adversarial win-lose scenario typical of gambling. Instead, mining competition is more akin to market competition, where success does not necessitate another's loss. Investment and loss: the argument that miners face a total loss in the absence of rewards was countered by the understanding that investments in mining infrastructure and operations constitute business expenses rather than gambles, with inherent value and potential for future gains. Chance versus effort: The role of chance in mining does not align with the gambling criterion of reliance on pure luck, as mining involves significant preparatory effort, investment, and an ongoing contribution to network maintenance. These findings collectively argue against the classification of cryptocurrency mining as gambling within the framework of Imamia Jurisprudence, highlighting the nuanced understanding required to evaluate modern financial technologies through the lens of traditional religious law. ‌ ∴ Conclusion ∴ ‌ The exhaustive investigation into the parallels between gambling characteristics and cryptocurrency mining concluded a significant divergence between the two under Imamia Jurisprudence. The research established that cryptocurrency mining does not embody the essential elements of gambling, namely, reliance on chance, direct financial wagering, and lack of productive contribution. Instead, mining is characterized by its integral role in the maintenance and security of the blockchain network, necessitating significant effort, investment, and skill. However, the conclusion that mining does not equate to gambling does not automatically confer legitimacy on all aspects of cryptocurrency operations within an Islamic context. The research underscores the need for further scholarly examination on other concerns related to cryptocurrency, such as the legitimacy of earnings and the intrinsic value of digital currencies. In essence, this study not only clarifies the position of cryptocurrency mining in relation to gambling within Imamia Jurisprudence but also opens avenues for further research into the broader ethical and economic implications of cryptocurrencies. It serves as a foundational piece for ongoing dialogue and exploration in the intersection of technology, finance, and religious ethics, emphasizing the importance of informed, nuanced scholarship in addressing contemporary issues through the lens of traditional jurisprudence.

Cryptocurrency has become a pivotal player in global financial transactions due to its decentralized mining process, which eliminates the need for intermediaries. However, the operation of cryptocurrency mining devices (CMDs) requires significant electrical power, leading to an increase in network-connected cryptocurrency mining loads (CMLs) that pose challenges for power grid operators. This paper evaluates the integration of CMLs into power grids, focusing on distribution network performance. A technology-accepted model for assessing cryptocurrency mining performance is presented, along with an analysis of the impacts of high CML penetration on power grid planning and operation. Findings reveal that high CML penetration can complicate load forecasting, congest transmission lines, and increase the coincident peak load in distribution networks. A case study of Iran’s power network indicates that CMLs account for approximately 2.8% of the nation’s electricity consumption. Furthermore, if 5% of residential customers in Tehran install CMDs, the average coincident peak demand for this group rises by 26.81%. Additionally, the average power factor of a sample CMD is about 0.99, while total current distortion and third harmonic current exceed permissible limits, indicating potential power quality issues. This study highlights the challenges posed by CMLs and proposes strategies for their sustainable integration into power grids.

This paper investigates the role of the materiality of computation in two domains: blockchain technologies and artificial intelligence (AI). Although historically designed as parallel computing accelerators for image rendering and videogames, graphics processing units (GPUs) have been instrumental in the explosion of both cryptoasset mining and machine learning models. The political economy associated with video games and Bitcoin and Ethereum mining provided a staggering growth in performance and energy efficiency and this, in turn, fostered a change in the epistemological understanding of AI: from rules-based or symbolic AI towards the matrix multiplications underpinning connectionism, machine learning and neural nets. Combining a material political economy of markets with a material epistemology of science, the article shows that there is no clear-cut division between software and hardware, between instructions and tools, and between frameworks of thought and the material and economic conditions of possibility of thought itself. As the microchip shortage and the growing geopolitical relevance of the hardware and semiconductor supply chain come to the fore, the paper invites social scientists to engage more closely with the materialities and hardware architectures of 'virtual' algorithms and software. [ABSTRACT FROM AUTHOR]

A search‐theoretic model is constructed, where money and Bitcoin can be used as mediums of exchange. We investigate how each currency facilitates transactions and how they compete with each other. Quantitative analysis shows that welfare in an economy with both money and Bitcoin is lower than in a money‐only economy due to congestions in the confirmation of Bitcoin transactions and that the welfare gap between the two economies expands as inflation rises. Moreover, an increase in transaction fees for Bitcoin can increase welfare by reducing inefficient Bitcoin transactions. [ABSTRACT FROM AUTHOR]

This study examines blockchain technologies and their pivotal role in the evolving Metaverse, shedding light on topics such as how to invest in cryptocurrency, the mechanics behind crypto mining, and strategies to effectively buy and trade cryptocurrencies. While it contextualises the common queries of "why is crypto crashing?" and "why is crypto down?", the research transcends beyond the frequent market fluctuations to unravel how cryptocurrencies fundamentally work and the step-by-step process on how to create a cryptocurrency. Contrasting existing literature, this comprehensive investigation encompasses both the economic and cybersecurity risks inherent in the blockchain and fintech spheres. Through an interdisciplinary approach, the research transitions from the fundamental principles of fintech investment strategies to the overarching implications of blockchain within the Metaverse. Alongside exploring machine learning potentials in financial sectors and risk assessment methodologies, the study critically assesses whether developed or developing nations are poised to reap greater benefits from these technologies. Moreover, it probes into both enduring and dubious crypto projects, drawing a distinct line between genuine blockchain applications and Ponzi-like schemes. The conclusion resolutely affirms the staying power of blockchain technologies, underlined by a profound exploration of their intrinsic value and a reflective commentary by the author on the potential risks confronting individual investors. [ABSTRACT FROM AUTHOR]

While volatility spillover is a vital research area in financial economics (due to its importance for risk valuation and portfolio diversification strategies), the volatility linkage between Bitcoin and electricity/energy markets has not received adequate attention. As the Bitcoin mining cost comes mainly from electricity (which is highly dependent on natural gas), we hypothesize that natural gas is a non-trivial Bitcoin price volatility driver and aim to test if this is the case. Specifically, we employ a widely used model called the HAR-RV model to assess volatility spillover across Bitcoin and natural gas using high-frequency data. We find a spillover effect from natural gas to Bitcoin, and the positive (negative) component of natural gas volatility stabilizes (destabilizes) Bitcoin volatility. The spillover effect is further examined and confirmed using an out-of-sample approach. [ABSTRACT FROM AUTHOR]

The cryptocurrency mining sector in Kazakhstan has witnessed remarkable expansion, attracting global miners due to favourable conditions. However, this growth has underscored the country’s energy scarcity, leading to the enforcement of stringent regulations by the government. This article seeks to offer a thorough comprehension of the regulatory framework governing cryptocurrency mining in Kazakhstan. Examining diverse aspects such as the legal status of mining, licensing structures, tax considerations, and the impact on energy infrastructure, the study utilizes international experiences and stimulus materials. Through the analysis of media representation and examination of primary trends, it is revealed that while the government has addressed legal gaps and instituted transparent tax procedures, taxing digital mining may discourage foreign investments, given the industry’s current fragility due to excessive regulations. The article provides insights into the regulatory landscape, emphasizing challenges and opportunities. [ABSTRACT FROM AUTHOR]

This document highlights the need for clear regulation in the cryptocurrency market. It emphasizes the importance of determining whether cryptocurrencies should be classified as commodities or securities, as this classification affects various aspects of the industry. The document suggests that the Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC) should engage in rulemaking to adapt existing rules or create new ones that align with the unique characteristics of cryptocurrencies. It also emphasizes the need for legislative guidance and public input to establish a formal regulatory framework that balances economic innovation and consumer protection. [Extracted from the article]

In this study, we used a combination of AI-assisted analysis of social media discourse and collaboration with industry experts to delve into the key research needs associated with the Bitcoin mining industry. We identified primary threats, opportunities, and research questions related to the Bitcoin mining industry and its wider impacts, focusing on its energy use and environmental footprint. Our findings spotlight the industry's move towards increasingly greater energy efficiency and an emerging commitment to renewable energy, highlighting its potential to contribute to the coming energy transition. We underscore the transformative potential of emerging applications in the Bitcoin mining sector, especially regarding demand response, grid flexibility, and methane mitigation. We suggest that targeted research on Bitcoin can serve policymakers, private sector decision-makers, research funding agencies, environmental scientists, and the Bitcoin industry itself. We propose that filling key information gaps could help clarify the risks and benefits of Bitcoin mining by encouraging collaboration among researchers, policymakers, and industry stakeholders and conducting research that provides baseline peer-reviewed evidence surrounding Bitcoin's production and impacts. A collaborative approach could help mitigate the risks and realize the benefits of Bitcoin mining, including potentially positive and substantive contributions in alignment with the Sustainable Development Goals. [ABSTRACT FROM AUTHOR]

This study estimates the environmental impacts of Bitcoin mining. Employing a top-down measurement approach, this paper assesses the carbon footprint of Bitcoin mining in China from 2017 to 2021. The findings reveal that mining activities during this period contributed to a total of 77.84 million tons of carbon dioxide emissions in China. By utilizing data at the provincial level, we find that the seasonal migration of Bitcoin mining pools will lead to regional power demand shocks in China. Additionally, this study predicts future carbon emissions from Bitcoin mining in China, projecting cumulative carbon dioxide emissions of 76.40 million tons and 722.18 million tons by 2030 and 2060 respectively, in the absence of any policy interventions. Based on these findings, this paper posits that governments worldwide should make efforts to restrict the carbon emissions from Bitcoin mining and opt for environmentally friendly technological methods to fundamentally alleviate Bitcoin's reliance on energy. The implication for central banks is that carbon emission should be taken into consideration when designing the central bank digital currencies (CBDCs). [ABSTRACT FROM AUTHOR]

This article aims to explore the co-movement of daily returns among S&P green bonds (GB/GBs), the top five sustainable cryptocurrencies, Bitcoin, the Dow Jones Sustainability World Index (DJSWI) and the Dow Jones Sustainability Emerging Market Index (DJSEMI) to determine whether GBs, Bitcoin and sustainable cryptocurrencies are truly sustainable; in addition, it investigates hedging and diversification opportunities. Using a partial wavelet coherence framework to capture the bivariate co-movement, our findings show strong (weak) positive co-movements among GB (sustainable cryptocurrencies) and DJSWI returns, where GBs (sustainable cryptocurrencies) have a heterogeneous leading role in the short-term and long-term horizons. Results indicate moderate positive (negative) co-movement among GBs and sustainable cryptocurrencies (Bitcoin) and DJSWI in the short run (long run). Overall, the results show GB (sustainable cryptocurrencies) acts as a diversifier for Bitcoin and sustainable cryptocurrencies in most cases (DJSWI). However, increasing Bitcoin returns adversely impacts the DJSWI in the long run. Findings are equally imperative for green investors, crypto traders and policymakers, where investors and traders can earn financial and social returns, and policy-makers can deploy suitable policies for the development of sustainable cryptocurrency mining processes. The role of Bitcoin is alarming for the United Nations Sustainable Development Goals and global greener economy. [ABSTRACT FROM AUTHOR]

Cryptojacking is a type of resource embezzlement attack, wherein an attacker secretly executes the cryptocurrency mining program in the target host to gain profits. It has been common since 2017, and in fact, it once became the greatest threat to network security. To better prove the attack ability the harm caused by cryptojacking, this paper proposes a new covert browser-based mining attack model named Delay-CJ, this model was deployed in a simulation environment for evaluation. Based on the general framework of cryptojacking, Delay-CJ adds hybrid evasion detection techniques and applies the delayed execution strategy specifically for video websites in the prototype implementation. The results show that the existing detection methods used for testing may become invalid as result of this model. In view of this situation, to achieve a more general and robust detection scheme, we built a cryptojacking detection system named CJDetector, which is based on cryptojacking process features. Specifically, it identifies malicious mining by monitoring CPU usage and analyzing the function call information. This system not only effectively detects the attack in our example but also has universal applicability. The recognition accuracy of CJDetector reaches 99.33%. Finally, we tested the web pages in Alexa 50K websites to investigate cryptojacking activity in the real network. We found that although cryptojacking is indeed on the decline, it remains a part of network security threats that cannot be ignored.

Bitcoin is always interesting to keep predicting where the next price movement will go. Bitcoin is the first and most influential Cryptocurrency on cryptocurrency price movements. Bitcoin is traded in many markets, the largest in Indonesia is Indodax. Indodax provides a document sharing API so that third parties can build applications that are able to process data on bitcoin price movements in real-time and continuously. This research shows how patterned datasets can be applied to monitor bitcoin price movements from the indodax market and show their effects on other cryptocurrency assets besides bitcoin. This research shows how data that is patterned and then processed using the minimum and maximum functions can provide 2 important information, namely the potential position of bitcoin when it is at the maximum and minimum points. The results of the patterned dataset formula are then compared to the movements of the 2 cryptocurrencies with the largest capitalization, namely BTC (Bitcoin) and ETH (Ethereum). The results of the comparison show that the use of patterned dataset formulas successfully shows important points in cryptocurrency trading, with simpler instructions. [ABSTRACT FROM AUTHOR]

This article explores the regulation of cryptocurrencies within the context of Competition Law. It analyzes the challenges that cryptocurrencies present to enforcement agencies, such as jurisdiction issues and market areas. The research findings can be used by policymakers and legal professionals to shape the regulatory framework for cryptocurrencies, promoting transparency and accountability. The article also discusses the decentralized nature of cryptocurrencies and the need for legal regulations to address their impact on the economy. It highlights the lack of clear regulations and guidelines for cryptocurrencies in India and suggests actions that competition authorities can take to ensure fair competition in the cryptocurrency economy. [Extracted from the article]

Purpose: While Blockchain can serve us, Bitcoin threatens our survival. If Bitcoin is assumed to be a country, it will rank 38th globally for energy consumption. With 90.2 metric million tonnes of carbon dioxide, Bitcoin mining and trading has emerged as an environmental threat. The current study investigates how the trading-specific variables, the prices of Crypto Index and Ethereum, affect bitcoin-based energy consumption. Also, the role of mining-specific variables is analyzed. Design/methodology/approach: The study uses monthly data from various sources collected from December 2018 to January 2023. The authors used the Autoregressive Distributed Lag (ARDL) Model to determine the short- and long-term relationships between variables. This study uses the Theory of Green Marketing and the Theory of Cross Elasticity of Demand as a theoretical lens. Findings: The findings show that escalating crypto market index and Ethereum prices with a one-month lag increases bitcoin-specific electricity consumption and carbon emissions. Green investors may shift to cryptocurrencies based on consensus other than of Proof-of-Work. Ethereum behaves like a substitute for Bitcoin, reflected by the long-term positive relationship between Bitcoin's energy consumption and Ethereum prices. Originality/value: The study analyses how the crypto market index and Ethereum price affect bitcoin-based energy use. The relationships identified are substantiated by the literature to provide suggestions to green investors and policymakers to mitigate the harmful impact of Bitcoin's colossal energy consumption on the natural environment. [ABSTRACT FROM AUTHOR]

Does the proof-of-work consensus protocol serve its intended purpose of supporting decentralized cryptocurrency mining? To address this question, we develop a game-theoretical model in which miners first invest in hardware to improve the efficiency of their operations and then compete for mining rewards in a rent-seeking game. We show that centralization grows with heterogeneity in mining costs, but hardware capacity constraints prevent the most efficient miners from monopolizing the mining process. Investment leads to a more decentralized network unless larger miners have a significant comparative advantage in acquiring new hardware. Our model generates empirically supported implications: (i) mining centralization is countercyclical with respect to mining reward, and (ii) a change in mining reward leads to a less-than-proportional change in hash rates. This paper was accepted by David Simchi-Levi, Special Section of Management Science: Blockchains and Crypto Economics. Supplemental Material: The data file is available at https://doi.org/10.1287/mnsc.2023.4840. [ABSTRACT FROM AUTHOR]

We assess how the cost structure of cryptocurrency mining affects the response of miners to exchange rate fluctuations and the immutability of cryptocurrency ledgers that rely on proof-of-work. We show that the amount of mining power supplied to currencies that rely on specialized hardware, such as Bitcoin, responds less to adverse exchange rate shocks than other currencies respond to such shocks, a fact that is instrumental to avoiding double-spending attacks. The results may change if mining equipment used for one cryptocurrency can be transferred to another. For smaller currencies with low exchange rate correlation, transferability eliminates the protection that fixed costs provide. Our results weaken doomsday predictions for Bitcoin and other cryptocurrencies with declining block rewards. This paper was accepted by Bruno Biais, Special Section of Management Science: Blockchains and Crypto Economics. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4901. [ABSTRACT FROM AUTHOR]