【Author】 Liao, Xin Wu, Hao He, Tiantian Luo, Xin
【影响因子】11.471
【主题类别】
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【Abstract】Cryptocurrency services, as one of the most successful applications of blockchain technology, have recently garnered significant attention from the graph learning community. Its large-scale dynamic transaction records contain a variety of behavioral patterns and rich knowledge involving accounts, making the dynamic cryptocurrency transaction network embedding (DCTNE) a hot, yet thorny research topic. As the trading accounts increase and time accumulates, considerable transaction services are dispersed into various time slots, leading to very sparse transaction data within a time slot, that is, the transaction service data is high-dimensional and incomplete (HDI). To efficiently mine high-value knowledge from HDI data, this article proposes a proximal-ADMM-incorporated nonnegative latent-factorization-of-tensors (PNL) model for DCTNE that adopts threefold ideas: 1) incorporating the proximal terms into the alternating-direction-method-of-multipliers (ADMMs)-based learning scheme to reduce the oscillations for high estimation accuracy and fast convergence; 2) implementing a parallel training process with hyperparameter self-adaptation for high computational efficiency; and 3) proving that the proximal-incorporated learning scheme guarantees the convergence to a Karush-Kuhn-Tucker (KKT) stationary point. Experimental results on eight real-world DCTNs show that the PNL significantly outperforms several state-of-the-art (SOTA) models, demonstrating not only high efficiency and accuracy in performing DCTNE, but also strong potential to enhance the operational reliability and stability of cryptocurrency transaction systems.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Cryptocurrency; Tensors; Convergence; Computational modeling; Adaptation models; Accuracy; Vectors; Representation learning; Blockchains; Spatiotemporal phenomena; Cryptocurrency service; dynamic cryptocurrency transaction network (DCTN); graph learning; high-dimensional and incomplete (HDI) data; network embedding; nonnegative latent-factorization-of-tensors (NLFTs); proximal alternating direction method of multipliers
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【Author】 Conlon, Thomas Corbet, Shaen
【影响因子】9.848
【主题类别】
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【Abstract】We investigate the contagion effects of rapid memecoin growth, a phenomenon often characterised by irrational exuberance and illicit behaviour. Using an EGARCH methodology, the results indicate that while memecoin growth generates revenue for host platforms like Ethereum and Solana, it broadly increases market-wide risk and is detrimental to established cryptocurrencies, such as Bitcoin. Furthermore, we find that PolitiFi memecoins are uniquely susceptible, characterised by positive responses to broad memecoin growth, exhibiting statistical properties deeming them attractive due to the cloaking provided by wider memecoin market growth, without evidence for tangible purposes.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Cryptocurrency; Memecoins; Contagion; Financial stability; PolitiFi
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【影响因子】9.224
【主题类别】
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【Abstract】Bitcoin, the pioneering decentralized currency, has transformed global finance. However, its expanding network drives greenhouse gas emissions, water use, and land consumption, posing sustainability challenges. This study introduces a novel methodological framework to assess these impacts across participating nations, integrating the ReCiPE 2016 midpoint (H) method for life cycle impact assessment of offsite environmental footprints and mathematical modeling for onsite environmental footprints, using open LCA and the Ecoinvent v3.10 database in a cradle-to-gate approach. The findings reveal that the United States, China, and Kazakhstan, responsible for 65% of global Bitcoin mining, are the largest contributors to its environmental impact. The United States records a water footprint of 419 million cubic meters under high computational load, enough to meet the annual water needs of Antigua and Barbuda, Barbados, and Bhutan. China leads with a 900 km2 land footprint, while Kazakhstan emits over 25 MtCO2e greenhouse gas emissions, driven by coal reliance. These findings offer policymakers region-specific insights to balance Bitcoin's economic benefits with its environmental costs, emphasizing the need for technological advancements and sustainable energy shifts. The study also calls for future research into pinpointing the Bitcoin miners' locations and the true computational mix of the global Bitcoin network.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】cryptocurrency; environmentalfootprint; digitalsystems; life cycle assessment; bitcoin mining
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【影响因子】8.702
【主题类别】
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【Abstract】Blockchain technology has been increasingly adopted in supply chains, offering new avenues for enhancing information transparency. This article investigates the role of blockchain in reducing consumer uncertainty, as well as its impact on competition between online and offline retailers under different market structures, using a game-theoretical approach. It highlights how blockchain enhances transparency and consumer trust, thereby influencing market dynamics and pricing strategies. The model incorporates consumer heterogeneity in terms of blockchain awareness and perceived product value, examining how these factors affect blockchain adoption decisions. A key finding reveals that blockchain can provide competitive advantages to online retailers, especially when consumer acceptance of the online channel is relatively low. Interestingly, if the online retailer adopts blockchain, higher mismatch costs could unexpectedly hurt profits. Moreover, our analysis shows that blockchain adoption does not necessarily benefit all retailers. Its effectiveness depends on consumer trust levels, awareness, and the magnitude of mismatch risks. Overall, this article offers managerial insights for retailers to tailor blockchain strategies based on market conditions, emphasizing the importance of consumer uncertainty and aligning blockchain's benefits with specific market roles.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Costs; Uncertainty; Production; Privacy; Numerical models; Transportation; Training; Systematic literature review; Supply chains; Blockchain; consumer uncertainty; game theory; market competition
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【DOI】 10.1109/TEM.2025.3599233
CCF-A
【影响因子】6.791
【主题类别】
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【Abstract】Blockchain systems have evolved over decades, addressing the inefficiencies and high costs associated with centralized architectures. Among various consensus mechanisms, committee-based hybrid Byzantine Fault Tolerant (BFT) protocols are a fundamental approach to blockchain consensus. However, designing a hybrid BFT consensus protocol that ensures fairness, responsiveness, and formal security remains challenging. In this paper, we propose GRBFT: a Gaussian reputation-based hybrid BFT blockchain consensus protocol with a formal security framework. Our proposed protocol integrates a multilateral Gaussian reputation evaluation to incentivize trusted nodes' participation in the consensus. We use threshold signatures and verifiable random functions (VRFs) to randomly select committee members and leaders, ensuring fair reconfiguration and unbiased sortition. A formal security framework is utilized to design and analyze the blockchain consensus system. Additionally, we design a speculative GRBFT (S-GRBFT) protocol to circumvent the traditional O(n(2)) leader sortition complexity and reduce the communication to O(n) within a single round. Moreover, we present a secure candidate committee reconfiguration method that efficiently updates members based on their reputation and a Proof-of-Stake (PoS) mechanism. The proposed GRBFT protocol is proven to achieve consistency and liveness under the corruption and liveness parameters.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Security; Consensus protocol; Complexity theory; Consensus algorithm; Proof of stake; Costs; Throughput; Bitcoin; Voting; Heuristic algorithms; Blockchain; Byzantine fault-tolerant (BFT); consensus; formal framework; Gaussian reputation; proof-of-stake (PoS); responsiveness
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【Author】 Yoo, Taehoon Kim, Kiseok Kim, Hwangnam
CCF-C
【影响因子】5.047
【主题类别】
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【Abstract】Blockchain technology has revolutionized distributed ledger systems by offering superior security and transparency compared to traditional centralized systems. Despite its advantages, current blockchain systems face significant challenges such as network congestion, communication errors, and scalability issues, largely due to the limitations of blockchain peer-to-peer (P2P) protocols. These problems hinder the performance, reliability, and widespread adoption of blockchain technology. In this paper, we propose a Trust-Defined Network (TDN) framework designed to solve these challenges by reflecting the physical network information to the blockchain. This approach enables the precise diagnosis of existing blockchain P2P protocol limitations and facilitates the objective verification of new improvement measures. Our proposed framework supports various blockchain network environments, particularly Ethereum-based networks, and ensures enhanced network stability and performance. Through extensive simulations and real-world case studies in IoT-enabled blockchain applications, we demonstrate that TDN significantly reduces network congestion, improves transaction finality, and enhances the reliability of blockchain communication channels. These findings highlight the framework's potential to optimize blockchain infrastructure, making it more robust for large-scale deployment and real-world applications.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Physical network information; Trust-Defined Network; P2P protocol; Network optimization
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【Author】 Sharma, Trishie Shukla, Sandeep Kumar
CCF-B
【影响因子】3.989
【主题类别】
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【Abstract】Amid the surge of Non-Fungible Tokens (NFTs) in blockchain, this study introduces a meticulous method-ology focusing on transaction behaviors to unveil rug pulls - a critical issue impacting financial securityand trust in the NFT landscape. Using a Graph Isomorphism Network (GIN) model with 6 behavioral pat-terns obtained from transaction sequences, we create a "Rug Pull Pattern Matcher" model. We provide acomprehensive analysis by applying the model on two datasets - creator's transactions from 50 reputableNFT projects and 32 reported rug pulls. Our work utilizes automated labeling to categorize addresses and ouranalysis reveals several interconnected NFT creator activities. We present an in-depth mapping of fund flowsand creator interactions exposing suspicious behaviors like artificial inflation and intricate network collab-orations among creators. The results of our proposed model demonstrate the efficacy of our methodologywith 75.4% accuracy and 85.9% precision on the dataset of reported rug pulls. This work provides compara-tive analyses of genuine and malicious creator networks to elucidate their structural differences, helping toidentify genuine and potentially fraudulent NFT activities.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; cryptocurrency frauds; ethereum; graph theory; illicit activi-ties; non-fungible tokens; rug pull
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【DOI】 10.1145/3744561
【影响因子】2.303
【主题类别】
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【Abstract】Bitcoin is a distributed and decentralized network relying on a consensus mechanism to ensure the verification of transactions and network security. The PoW mechanism is integral to the process of mining Bitcoin transactions, where miners solve cryptographic puzzles using a process known as hashing. Hash functions play an important role in the PoW mechanism to ensure blockchain integrity, security, and efficiency. The speed of hash functions is one of the important factors that determine the processing time of transactions and mining of new blocks on PoW-based networks viz Bitcoin. This paper investigates the impact of various hash functions-SHA-256, Keccak-256, Blake2b, and Blake3 on mining speed in the Bitcoin network. The paper emphasizes not only the computational performance of hash functions but also assesses their security by analyzing their key security characteristics. Additionally, the energy requirements of each hash function are also analyzed. Our findings provide insights into how various hashing techniques affect the security and mining performance of blockchains, which is important information for protocol optimization.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Bitcoin; Blockchain; Cryptography; Hash functions; Proof-of-work (PoW); Security
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【Author】 Li, Boyi Xia, Weixuan
【影响因子】1.986
【主题类别】
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【Abstract】Recent empirical evidence has highlighted the crucial role of jumps in both price and volatility within the cryptocurrency market. In this paper, we integrate price-volatility co-jumps and volatility short-term dependency into a coherent model framework, featuring fractional stochastic volatility. We particularly focus on inverse options, including the emerging Quanto inverse options and their power-type generalizations, aiming at mitigating cryptocurrency exchange rate risk and adjusting inherent risk exposure. Characteristic function-based pricing-hedging formulas are derived for these inverse options. The model framework is applied to asymmetric Laplace jump-diffusions and Gaussian-mixed tempered stable-type processes, employing three types of fractional kernels, for an extensive empirical analysis involving model calibration on two independent Bitcoin options data sets, during and after the COVID-19 pandemic. Key insights from our theoretical analysis and empirical findings include: (1) the superior performance of fractional stochastic-volatility models compared to various benchmark models, including those incorporating jumps and stochastic volatility, along with high computational efficiency when utilizing a piecewise kernel, (2) the practical necessity of considering jumps in both price and volatility, along with rough volatility, in pricing and hedging cryptocurrency options, (3) stability of calibrated parameter values in line with stylized facts.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Cryptocurrency market; Quanto inverse-power options; Fractional volatility; Correlated jump risk; Piecewise kernel; G13; C65; C52
【发表时间】2025
【收录时间】2025-09-29
【文献类型】
【影响因子】0.612
【主题类别】
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【Abstract】The interaction of ecology and science is clear; that with computing, much less so, other than as an analytic tool. But increasingly severe overconsumption of natural resources, primarily power and water, by applications, including generative artificial intelligence, very large databases and data analytics, and cryptocurrency, presents a serious ethical challenge. In specific instances, this may be balanced, ethically and practically, by the good achieved, especially for environmental issues. Even then, local concerns arise, such as environmental racism. In this paper, we apply Catholic Social Teaching (CST) and other traditions and provide recommendations for ethical use of these technologies.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Computing resource use; artificial intelligence; generative AI; data analytics; blockchain; environmental ethics; catholic social teaching
【发表时间】2025
【收录时间】2025-09-29
【文献类型】