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Keywords = bitcoin hash rate

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27 pages, 1230 KiB  
Article
Proof of Work with Random Selection (PoWR): An Energy Saving Consensus Algorithm with Proof of Work and the Random Selection Function
by Jin Woo Jung, Md. Mainul Islam and Hoh Peter In
Sustainability 2024, 16(21), 9342; https://doi.org/10.3390/su16219342 - 28 Oct 2024
Cited by 1 | Viewed by 2541
Abstract
Bitcoin, which has been used for 13 years, has a role in transactions and investments as a major cryptocurrency. However, as the number of users increases, Bitcoin faces difficulties, such as scalability for transaction throughput and energy-consumption problems due to the concentration of [...] Read more.
Bitcoin, which has been used for 13 years, has a role in transactions and investments as a major cryptocurrency. However, as the number of users increases, Bitcoin faces difficulties, such as scalability for transaction throughput and energy-consumption problems due to the concentration of the mining pool. When Bitcoin first started to come out, it began to develop gradually through the mining of individuals. Nevertheless, as the price of the cryptocurrency gradually climbed, large mining corporation groups entered the mining competition with integrated circuit (IC) chips. Consequently, the substantial increase in power consumption is raising concerns regarding energy expenditure. This paper confirms that the verifiable random selection consensus protocol based on proof of work facilitates a fair and efficient system, enabling the participation of numerous individual miners in the mining competition while counteracting the monopolization of the hash rate by large mining corporations, thereby preserving the decentralization of mining. The protocol demonstrates the potential to mitigate substantial energy consumption. Moreover, it embodies features that create barriers to the adoption of high-energy-consuming application-specific integrated circuit equipment, significantly diminishing the principal factors contributing to extensive power utilization. Full article
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37 pages, 8647 KiB  
Article
Forecasting of Bitcoin Illiquidity Using High-Dimensional and Textual Features
by Faraz Sasani, Mohammad Moghareh Dehkordi, Zahra Ebrahimi, Hakimeh Dustmohammadloo, Parisa Bouzari, Pejman Ebrahimi, Enikő Lencsés and Mária Fekete-Farkas
Computers 2024, 13(1), 20; https://doi.org/10.3390/computers13010020 - 9 Jan 2024
Cited by 3 | Viewed by 2937
Abstract
Liquidity is the ease of converting an asset (physical/digital) into cash or another asset without loss and is shown by the relationship between the time scale and the price scale of an investment. This article examines the illiquidity of Bitcoin (BTC). Bitcoin hash [...] Read more.
Liquidity is the ease of converting an asset (physical/digital) into cash or another asset without loss and is shown by the relationship between the time scale and the price scale of an investment. This article examines the illiquidity of Bitcoin (BTC). Bitcoin hash rate information was collected at three different time intervals; parallel to these data, textual information related to these intervals was collected from Twitter for each day. Due to the regression nature of illiquidity prediction, approaches based on recurrent networks were suggested. Seven approaches: ANN, SVM, SANN, LSTM, Simple RNN, GRU, and IndRNN, were tested on these data. To evaluate these approaches, three evaluation methods were used: random split (paper), random split (run) and linear split (run). The research results indicate that the IndRNN approach provided better results. Full article
(This article belongs to the Special Issue Uncertainty-Aware Artificial Intelligence)
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22 pages, 3682 KiB  
Article
An Adoptive Miner-Misuse Based Online Anomaly Detection Approach in the Power System: An Optimum Reinforcement Learning Method
by Abdulaziz Almalaq, Saleh Albadran and Mohamed A. Mohamed
Mathematics 2023, 11(4), 884; https://doi.org/10.3390/math11040884 - 9 Feb 2023
Cited by 7 | Viewed by 1761
Abstract
Over the past few years, the Bitcoin-based financial trading system (BFTS) has created new challenges for the power system due to the high-risk consumption of mining devices. Briefly, such a problem would be a compelling incentive for cyber-attackers who intend to inflict significant [...] Read more.
Over the past few years, the Bitcoin-based financial trading system (BFTS) has created new challenges for the power system due to the high-risk consumption of mining devices. Briefly, such a problem would be a compelling incentive for cyber-attackers who intend to inflict significant infections on a power system. Simply put, an effort to phony up the consumption data of mining devices results in the furtherance of messing up the optimal energy management within the power system. Hence, this paper introduces a new cyber-attack named miner-misuse for power systems equipped by transaction tech. To overwhelm this dispute, this article also addresses an online coefficient anomaly detection approach with reliance on the reinforcement learning (RL) concept for the power system. On account of not being sufficiently aware of the system, we fulfilled the Observable Markov Decision Process (OMDP) idea in the RL mechanism in order to barricade the miner attack. The proposed method would be enhanced in an optimal and punctual way if the setting parameters were properly established in the learning procedure. So to speak, a hybrid mechanism of the optimization approach and learning structure will not only guarantee catching in the best and most far-sighted solution but also become the high converging time. To this end, this paper proposes an Intelligent Priority Selection (IPS) algorithm merging with the suggested RL method to become more punctual and optimum in the way of detecting miner attacks. Additionally, to conjure up the proposed detection approach’s effectiveness, mathematical modeling of the energy consumption of the mining devices based on the hashing rate within BFTS is provided. The uncertain fluctuation related to the needed energy of miners makes energy management unpredictable and needs to be dealt with. Hence, the unscented transformation (UT) method can obtain a high chance of precisely modeling the uncertain parameters within the system. All in all, the F-score value and successful probability of attack inferred from results revealed that the proposed anomaly detection method has the ability to identify the miner attacks as real-time-short as possible compared to other approaches. Full article
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18 pages, 7721 KiB  
Article
Based on the Time-Spatial Power-Based Cryptocurrency Miner Driving Force Model, Establish a Global CO2 Emission Prediction Framework after China Bans Cryptocurrency
by Xuejia Sang, Xiaopeng Leng, Linfu Xue and Xiangjin Ran
Sustainability 2022, 14(9), 5332; https://doi.org/10.3390/su14095332 - 28 Apr 2022
Cited by 9 | Viewed by 4681
Abstract
The energy consumption and carbon footprint of cryptocurrencies have always been a popular topic. However, most of the existing studies only focus on one cryptocurrency, Bitcoin, and there is a lack of long-term monitoring studies that summarize all cryptocurrencies. By constructing a time [...] Read more.
The energy consumption and carbon footprint of cryptocurrencies have always been a popular topic. However, most of the existing studies only focus on one cryptocurrency, Bitcoin, and there is a lack of long-term monitoring studies that summarize all cryptocurrencies. By constructing a time series hash rate/power model, this research obtained the 10-year time series data on energy consumption dataset of global top-25 cryptocurrencies for the first time. Both the temporal coverage and the spatiotemporal resolution of the data exceed previous studies. The results show that Bitcoin’s power consumption only accounts for 58% of the top-25 cryptocurrencies. After China bans cryptocurrencies, the conservative change in global CO2 emissions from 2020 will be between −0.4% and 4.4%, and Central Asian countries such as Kazakhstan are likely to become areas of rapid growth in carbon emissions from cryptocurrencies. Full article
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18 pages, 5861 KiB  
Article
ECCPoW: Error-Correction Code based Proof-of-Work for ASIC Resistance
by Hyunjun Jung and Heung-No Lee
Symmetry 2020, 12(6), 988; https://doi.org/10.3390/sym12060988 - 9 Jun 2020
Cited by 11 | Viewed by 4433
Abstract
Bitcoin is the first cryptocurrency to participate in a network and receive compensation for online remittance and mining without any intervention from a third party, such as financial institutions. Bitcoin mining is done through proof of work (PoW). Given its characteristics, the higher [...] Read more.
Bitcoin is the first cryptocurrency to participate in a network and receive compensation for online remittance and mining without any intervention from a third party, such as financial institutions. Bitcoin mining is done through proof of work (PoW). Given its characteristics, the higher hash rate results in a higher probability of mining, leading to the emergence of a mining pool, called a mining organization. Unlike central processing units or graphics processing units, high-cost application-specific integrated circuit miners have emerged with performance efficiency. The problem is that the obtained hash rate exposes Bitcoin’s mining monopoly and causes the risk of a double-payment attack. To solve this problem, we propose the error-correction code PoW (ECCPoW), combining the low-density parity-check decoder and hash function. The ECCPoW contributes to the phenomenon of symmetry in the proof of work (PoW) blockchain. This paper proposes the implementation of ECCPoW, replacing the PoW in Bitcoin. Finally, we compare the mining centralization, security, and scalability of ECCPoW and Bitcoin. Full article
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22 pages, 2666 KiB  
Article
Data Query Mechanism Based on Hash Computing Power of Blockchain in Internet of Things
by Yongjun Ren, Fujian Zhu, Pradip Kumar Sharma, Tian Wang, Jin Wang, Osama Alfarraj and Amr Tolba
Sensors 2020, 20(1), 207; https://doi.org/10.3390/s20010207 - 30 Dec 2019
Cited by 144 | Viewed by 7086
Abstract
In the IoT (Internet of Things) environment, smart homes, smart grids, and telematics constantly generate data with complex attributes. These data have low heterogeneity and poor interoperability, which brings difficulties to data management and value mining. The promising combination of blockchain and the [...] Read more.
In the IoT (Internet of Things) environment, smart homes, smart grids, and telematics constantly generate data with complex attributes. These data have low heterogeneity and poor interoperability, which brings difficulties to data management and value mining. The promising combination of blockchain and the Internet of things as BCoT (blockchain of things) can solve these problems. This paper introduces an innovative method DCOMB (dual combination Bloom filter) to firstly convert the computational power of bitcoin mining into the computational power of query. Furthermore, this article uses the DCOMB method to build blockchain-based IoT data query model. DCOMB can implement queries only through mining hash calculation. This model combines the data stream of the IoT with the timestamp of the blockchain, improving the interoperability of data and the versatility of the IoT database system. The experiment results show that the random reading performance of DCOMB query is higher than that of COMB (combination Bloom filter), and the error rate of DCOMB is lower. Meanwhile, both DCOMB and COMB query performance are better than MySQL (My Structured Query Language). Full article
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20 pages, 732 KiB  
Article
Banking on Blockchain: Costs Savings Thanks to the Blockchain Technology
by Luisanna Cocco, Andrea Pinna and Michele Marchesi
Future Internet 2017, 9(3), 25; https://doi.org/10.3390/fi9030025 - 27 Jun 2017
Cited by 242 | Viewed by 34536
Abstract
This paper looks at the challenges and opportunities of implementing blockchain technology across banking, providing food for thought about the potentialities of this disruptive technology. The blockchain technology can optimize the global financial infrastructure, achieving sustainable development, using more efficient systems than at [...] Read more.
This paper looks at the challenges and opportunities of implementing blockchain technology across banking, providing food for thought about the potentialities of this disruptive technology. The blockchain technology can optimize the global financial infrastructure, achieving sustainable development, using more efficient systems than at present. In fact, many banks are currently focusing on blockchain technology to promote economic growth and accelerate the development of green technologies. In order to understand the potential of blockchain technology to support the financial system, we studied the actual performance of the Bitcoin system, also highlighting its major limitations, such as the significant energy consumption due to the high computing power required, and the high cost of hardware. We estimated the electrical power and the hash rate of the Bitcoin network, over time, and, in order to evaluate the efficiency of the Bitcoin system in its actual operation, we defined three quantities: “economic efficiency”, “operational efficiency”, and “efficient service”. The obtained results show that by overcoming the disadvantages of the Bitcoin system, and therefore of blockchain technology, we could be able to handle financial processes in a more efficient way than under the current system. Full article
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