Combining Indicators: Maximizing Mining Returns In Dallas Forex Strategies

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Combining Indicators: Maximizing Mining Returns In Dallas Forex Strategies – Fuzzy pressure control in a water supply network based on neural network system modeling and IoT measurements

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Combining Indicators: Maximizing Mining Returns In Dallas Forex Strategies

Combining Indicators: Maximizing Mining Returns In Dallas Forex Strategies

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Author: Yang Zhang Yang Zhang Scilit Preprints.org Google Scholar 1, 2, Yourong Chen Yourong Chen Scilit Preprints.org Google Scholar 1, Kelei Miao Kelei Miao Scilit Preprints.org Google Scholar 1, * , Tiaojuan Ren Tiaojuan Ren Scilit Preprints.org Google Scholar 1, Changchun Yang Changchun Yang Scilit Preprints.org Google Scholar 2 and Meng Han Meng Han Scilit Preprints.org Google Scholar 3, 4

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Received: October 28, 2022 / Revised: November 18, 2022 / Accepted: November 21, 2022 / Published: November 24, 2022

In the blockchain system, mining pools are popular for miners to work collectively and earn more income. Today, there are consensus attacks that threaten the efficiency and security of mining pools. As a new consensus attack, the Fork After Withholding (FAW) attack can cause huge financial losses to mining pools. Currently, there are a number of assessment tools for FAW attacks, but it is still difficult to assess the FAW attack protection capability of target mining pools. To address the above problem, this paper proposes a new evaluation framework for FAW attack protection of targeted mining pools in blockchain systems. In this framework, we establish a revenue model for mining pools, including honest consensus revenue, block retention revenue, successful fork revenue, and consensus cost. We also set the revenue for target mining pools and other mining pools, respectively. In particular, we propose an efficient computational power allocation optimization algorithm (CPAOA) for FAW attacks against multiple targeted mining pools. We propose a model solving algorithm based on the improved Aquila optimization, which can improve the selection mechanism in different optimization stages, increase the convergence speed of the model solution, and help find the optimal solution in the allocation of computing power. Furthermore, to greatly reduce the chance of falling into local optimal solutions, we propose a solution updating mechanism that combines the bee foragers’ idea into an artificial bee colony optimization algorithm and a computational power allocation constraint. Experimental results show that the framework can effectively evaluate the revenue of various mining pools. CPAOA can quickly and accurately allocate the computing power of FAW attacks based on the computing power of the target mining pool. Thus, the proposed evaluation framework can effectively help evaluate the FAW attack protection capability of multi-target mining pools and ensure the security of the blockchain system.

With the advancement of digitalization, the data security problem of centralized intelligent systems (such as data theft, privacy theft, and illegal operations) has occurred due to the centralized processing of massive data [1, 2, 3]. Due to the characteristics of decentralization, time series data, collective maintenance and immutability of blockchain technology, the security requirements of intelligent systems have promoted the development of blockchain technology [4]. Currently, blockchain technology is widely applied in the Internet of Things, smart healthcare, smart commerce, etc. [5, 6, 7]. Technology is crucial to accelerate the development of digital industrialization; blockchain technology significantly improves the efficiency and security of the digital industry. Today, academia and industry have focused their efforts on researching the strategic frontier technology of blockchain and applying it to digital reform [8].

Combining Indicators: Maximizing Mining Returns In Dallas Forex Strategies

Consensus algorithm is one of the basic blockchain technologies that can realize the consistency of massive network nodes in transactions [9]. Proof of Work (PoW) is one of the most widely used consensus algorithms. It has been applied to validate transactions and records of cryptocurrencies such as Bitcoin [10]. In the PoW process, miners must continuously solve mathematical puzzles with their computing power to earn block accounting rights. The more blocks there are in the entire network, the more difficult the mathematical puzzles for miners to solve. Thus, the probability of a single miner receiving income with his computing power will be lower, and a single miner will have to wait a long time to receive income. To receive more consistent income, some miners may choose to create mining pools. Within these pools, the pool manager concentrates all the miners to reach a consensus and distribute the income in proportion to each miner’s contribution. Although mining pools provide more stable income to miners, during the consensus process [11] mining pools can be subject to consensus attacks, such as Selfish Mining (SM) attack [12], Block Withholding (BWH) attack [13], and Fork After Holding (FAW) attack. Consensus attacks affect normal transactions in mining pools and provide transaction support for criminal activities such as money laundering, cyber extortion, etc. [14]. In the SM attack, the attacker does not emit the block after mining. When other miners have calculated the block, the attacker will immediately spread the mined block and compete for the income of the current block, which creates a fork in the blockchain, that is, the chain is divided into two branches [15]. However, the successful launch of SM attacks depends on the attacker’s high computing power and high block propagation efficiency. The BWH attacker allocates his computing power. It uses part of the computing power for common consensus and uses the rest of the computing power to access the target mining pool. Then only a part of the PoW is reported and the whole PoW is rejected [16]. The computing power to penetrate does not contribute to the target mining pools, but it still helps the attacker to collect the revenue distributed by the target mining pool. However, BWH attacks can cause mining pools to fall into the miner’s dilemma problem. The FAW attack is a new attack that combines SM attacks and BWH attacks [17]. In FAW attack, the attacker allocates his computing power as in BWH attacks. It uses some of the computing power to launch penetration attacks. But the attacker does not discard the whole PoW immediately and keep the block, as in SM attacks. When miners attacked by FAW know that it has been calculated and mined by other miners, they will immediately report the mined block and broadcast, thus creating a fork for revenue. The FAW attack turns the income of the BWH attack into a lower bound income and does not create the miner’s dilemma problem. Therefore, the FAW attack can help the attacker to gain revenue from BWH attacks, then reduce and reduce the target mining revenue. As a result, the FAW attack is a more threatening method against mining pools, which reduces the enthusiasm of mining pools for consensus and compromises the security of consensus.

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It is of great importance to analyze and evaluate the protection capability of target mining pools against FAW attacks, which can improve the security of network target mining pools. There are currently some results in the field of FAW attack evaluation. The main problems with traditional FAW attack assessment methods are:

Nowadays, some scholars use reinforcement learning, optimization, strategy selection and other methods to study BWH attacks or SM attacks. For example, Fan et al. [18] proposed an adaptive zero-determinant strategy that calculates the revenue of the cooperative strategy and the betrayal strategy by calculating the cooperative strategy. The revenue method solves the problem of mutual BWH attacks between mining pools and non-cooperative mining. Davidson et al. [19] proposed an SM strategy based on chains of variable difficulty. This strategy generalizes to different mining difficulties and the importance of making block timestamp manipulation a new component of the strategy space for selfish miners. Current relevant benchmarks may better implement BWH attacks or SM attacks, but BWH attacks will fall into the miner’s dilemma in mining pools in practice. Successfully launching an SM attack requires high computing power on the part of the attacker

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