Abstract When Nakamoto invented Bitcoin, the first generation of cryptocurrencies followed it in applying POW (Proof of Work) consensus mechanism; due to its excessive energy consumption and heavy carbon footprints, new innovations evolved like Proof of Space , POS (Proof of Stake) , and a lot more with many variants for each. Furthermore, the emergence of more blockchain applications and kinds beyond just cryptocurrencies needed more consensus mechanisms that is optimized to fit requirements of each application or blockchain kind; examples range from IoT (Internet of Things) blockchains for sustainability applications that often use variants of BFT (Byzantine Fault Tolerance) algorithm, and consensus needed to relay transactions and/or assets between different blockchains in interoperability solutions. Previous studies concentrated on surveying and/or proposing different blockchain consensus rules, on a specific consensus issue like attacks, randomization, or on deriving theoretical results. Starting from discussing most important theoretical results, this paper tries to gather and organize all significant existing material about consensus in the blockchain world explaining design challenges, tradeoffs and research areas. We realize that the topic could fit for a complete textbook, so we summarize the basic concepts and support with tables and appendices. Then we highlight some case examples from interoperability solutions to show how flexible and wide the design space is to fit both general and special purpose systems. The aim is to provide researchers with a comprehensive overview of the topic, along with the links to go deeper into every detail.
Tan Khai Lian, Ismail Ahmad Al-Qasem Al-Hadi, Mohammad Ahmed Alomari, Mohammed Nasser Al-Andoli · 6 authors
Bitcoin has recently emerged as a leading asset in the cryptocurrency market. However, its significant price volatility presents challenges for accurate prediction. Due to this volatility, forecasting Bitcoin prices accurately is difficult and complicates decision-making for investors and traders in the cryptocurrency space. This research compares the accuracy of three prediction models: Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Facebook's NeuralProphet, introduced in 2021, focusing on improving Bitcoin price forecasting accuracy. The study uses daily Bitcoin prices from the past five years to assess model performance. Results indicate that the LSTM model outperforms both NeuralProphet and RNN in prediction accuracy. This comparison holds substantial economic significance, as accurate predictions can assist investors and traders in making informed decisions within the cryptocurrency market.
This working paper introduces the Blockchain First-Principles Analysis (BFPA) framework, a novel methodology for evaluating distributed ledger systems by constructing explicit derivation chains from physical laws and cryptographic assumptions through a praxeological action axiom to concrete protocol design decisions. The framework features a four-level axiom hierarchy (physics, cryptography, praxeology, social consensus), a Nash equilibrium gate for social layer stability, a four-stage stability profile, a lock-in typology distinguishing design-emergent, ecosystem-emergent, corporate-imposed, and regulatory-granted lock-in, and a network effect genesis model identifying five necessary conditions for spontaneous adoption. Systematic application to eight major blockchain systems (Bitcoin, Ethereum, Solana, Monero, XRP, Polkadot, Tezos, BNB Chain) reveals that epistemic design quality correlates weakly with market outcomes, while lock-in type and network effect genesis conditions are substantially stronger predictors. The analysis provides principled explanations for the Tezos Paradox and the Monero Paradox. Comments welcome.
Abstract This study explores the higher-order moments of connectedness among cryptocurrency, commodity, bond, and stock markets from April 19, 2017, to December 29, 2023, on the basis of the GARCH-SK and TVP-VAR models. The findings reveal that Bitcoin and Ethereum act as significant net shock transmitters, especially during major events such as the COVID-19 pandemic and the Russia–Ukraine conflict. After mid-2021, these cryptocurrencies transitioned from net receivers to net transmitters of volatility owing to rising economic and geopolitical risks. These insights assist in portfolio diversification strategies. By combining shock transmitters with shock-resilient cryptocurrencies, investors can enhance their risk profiles. Diversification opportunities shift during financial crises, making it crucial to focus on shock transmitters, which are less influenced by various risk factors. Additionally, the study highlights cryptocurrencies as potential safe havens compared with traditional assets such as gold, bonds, and stocks, which often maintain or appreciate value during market stress. TVP-VAR-informed dynamic portfolio reallocation can improve risk-adjusted returns and lower volatility, aiding in capital preservation during high TCI periods. Overall, our findings suggest that portfolios that include cryptocurrencies generally outperform those that do not, emphasizing their role as effective diversifiers in portfolio optimization and financial stability.
Penelitian ini bertujuan untuk menganalisis pengaruh harga Bitcoin, Ethereum, indeks S&P 500, dan emas terhadap volatilitas harga Xrp. Xrp sebagai salah satu aset kripto dengan kapitalisasi pasar besar menunjukkan tingkat volatilitas yang tinggi, sehingga penting untuk memahami faktor-faktor eksternal yang memengaruhi pergerakan volatilitasnya. Penelitian ini menggunakan pendekatan kuantitatif dengan data sekunder berbentuk time series. Data yang digunakan meliputi harga Bitcoin, Ethereum, S&P 500, emas, serta harga Xrp yang diperoleh dari sumber terpercaya seperti Investing.com dan Coinglass selama periode pengamatan tertentu. Volatilitas harga Xrp dianalisis menggunakan model Multivariate Generalized Autoregressive Conditional Heteroskedasticity untuk menangkap karakteristik volatilitas yang bersifat time-varying, clustering, serta keterkaitan volatilitas antar aset. Hasil penelitian menunjukkan bahwa harga Bitcoin berpengaruh signifikan terhadap volatilitas harga Xrp, yang mengindikasikan adanya keterkaitan volatilitas yang kuat antara kedua aset kripto tersebut. Sementara itu, harga Ethereum, indeks S&P 500, dan emas tidak menunjukkan pengaruh signifikan terhadap volatilitas harga Xrp. Temuan ini mengindikasikan bahwa volatilitas Xrp lebih sensitif terhadap dinamika pergerakan Bitcoin dibandingkan dengan aset kripto lainnya maupun aset keuangan tradisional. Penelitian ini memberikan implikasi penting bagi investor dan pelaku pasar dalam pengambilan keputusan investasi, khususnya dalam mengelola risiko pada aset kripto. Selain itu, hasil penelitian ini diharapkan dapat menjadi referensi bagi penelitian selanjutnya terkait keterkaitan volatilitas antar aset kripto dan integrasinya dengan pasar keuangan global
Yaroslava Yakovenko, Zavodovska D., Reichling Peter
Over the past decade, cryptocurrencies have evolved from a niche technological innovation into a global financial phenomenon. Bitcoin, Ethereum, and other digital assets have attracted massive attention from investors, policymakers, and the general public. The central debate surrounding cryptocurrencies centres on whether they represent a financial bubble destined to burst or the foundation of a new, decentralized financial future.
This study explores the diversification potential of Bitcoin in a French investment portfolio comprising oil, currency, and gold across three distinct market regimes: a pre-crisis stable period, the COVID-19 pandemic, and the Russia–Ukraine conflict. The purpose is to assess whether Bitcoin can enhance portfolio efficiency and provide hedging opportunities under varying market conditions. The analysis is conducted using daily data for Bitcoin, gold, oil, currency, and the CAC40 index from January 1, 2019, to April 22, 2022. Portfolio performance is evaluated through the Mean–Variance (MV) framework and Stochastic Dominance (SD) analysis, allowing for a robust comparison of risk–return trade-offs and investor preferences. The MV results show that including Bitcoin consistently improves the portfolio’s risk–return profile, evidenced by an upward shift in the efficient frontier across all sub-periods. However, the SD analysis yields more nuanced insights. Before and during the COVID-19 crisis, the portfolio excluding Bitcoin dominates the Bitcoin-inclusive portfolio under second- and third-order stochastic dominance criteria, suggesting that risk-averse investors would prefer the traditional asset mix. In contrast, during the Russia–Ukraine war, no clear stochastic dominance is detected between Bitcoin-inclusive and Bitcoin-exclusive portfolios. These findings emphasize that Bitcoin’s diversification role is highly context- and framework-dependent.
Using the Crypto Fear & Greed Index and Bitcoin daily data, sentiment extremity predicts excess uncertainty beyond realized volatility. Extreme fear and extreme greed regimes exhibit significantly higher spreads than neutral periods -- the "extremity premium." Extended validation on the full Fear & Greed history (2018--2026, N = 2,896) confirms the finding: within-volatility-quintile comparisons show a premium ($p < 0.001$, pooled volatility-demeaned Cohen's $d = 0.21$ -- a post-hoc, exploratory test, as the pre-specified within-quintile endpoint does not survive multiple-testing correction; raw pooled extreme-vs-neutral $d = 0.40$), Granger causality runs from uncertainty to spreads (primary-sample $F = 12.79$; the extended-sample $F = 211$ is partly mechanical, sharing a high-low input with the spread measure), and placebo tests reject the null ($p < 0.0001$). The effect replicates on Ethereum and across 6 of 7 market cycles. However, the premium is sensitive to functional form: regression controls absorb regime effects, while nonparametric stratification preserves them. We interpret this as evidence that sentiment extremity captures volatility-regime interactions not fully represented by parametric controls -- consistent with, but not conclusively separable from, the F&G Index's embedded volatility component. An agent-based model is included as an illustrative device that reproduces the pattern qualitatively; because its spread-uncertainty link is coded rather than emergent, it does no inferential work (the reported moment-matching test validates a separate simplified model, not the full agent specification), and the inferential weight rests entirely on the empirical analysis. The results suggest that intensity, not direction, drives uncertainty-linked liquidity withdrawal in cryptocurrency markets, though identifying "pure" sentiment effects from volatility remains open.
Blockchain technology is a distributed ledger system providing secure, transparent, decentralized cryptocurrency transactions. Its underlying structure includes wallets and the Unspent Transaction Output (UTXO), which facilitates transactions and maintains transaction integrity. A blockchain wallet is a software program that stores and manages cryptocurrencies, allowing users to send and receive digital currency and monitor their balance. The UTXO set tracks unspent outputs, particularly in the Bitcoin network, ensuring accurate and secure accounting of available balances. This paper examines how well a hybrid data structure performs when processing wallet values in a UTXO set. The hybrid data structure stores the wallet’s addresses in a hash table and the UTXO in a minimum heap tree rather than a list. At first, we assume that the values in the list should always be sorted and appear in ascending order. Then, we employ a list with unsorted values. The wallet addresses are invariably assigned to a hash table. The “instruction count” approach counts the number of statements that can be executed or what we refer to as a “single operation” to measure performance.
The study focusses on cryptocurrency and asset recording in finance. In this cryptocurrency, digital currency which is the optional form of payment created using encryption algorithms. Cryptocurrency uses assets, intangible assets or property. They are some methods and challenges of assets. The data collected from primary and secondary sources. Secondary sources are journal, article, research paper, websites etc. In this study primary data collected through well-structural questionnaire which is collected from students of B.com 1st Yr, 2nd Yr, 3rd Yr and B.com (Hons) 2nd Yr, 3rd Yr. Simple Random sampling method are applied to collect the data from 110 respondents. My study area is Ramanand Institute of Pharmacy and Management College, Haridwar, Uttarakhand. 5point Likert scale applied in the study to measure the cryptocurrency and asset recording level of students about bitcoin, asset and currency. The finding of the study that cryptocurrency and asset recording in finance help students is selfdependent purpose and update growth level. After collecting data, analysis with the help of statistical tools such as percentage and graphical representation. The conclusion of the comparative study consistently shows that bitcoin, asset recording, investment in finance for the future planning.
Open access
Blockchain Technology Applications and Security
Cyberloafing and Workplace Behavior
Innovations and Analysis in Business and Education
Financial markets exhibit temporal organization that is not fully captured by volatility measures or linear correlation structure. We study a null-validated topological approach for quantifying financial market complexity using Bitcoin daily log returns and the S&P 500 index as examples of cryptocurrency and broad U.S. equity market dynamics. The analysis uses the $L^1$ norm of the persistence landscapes computed from sliding-window delay embeddings. This quantity co-moves strongly with stochastic volatility during periods of market stress, but the strength and form of this relationship vary over time and differ between the two markets. Surrogate-based null models provide statistical validation of these observations. Rejection of shuffle surrogates rules out explanations based on marginal distributions alone, while departures from phase randomized surrogates indicate sensitivity to nonlinear and phase-dependent temporal organization beyond linear correlations. These results demonstrate that persistence landscape norms provide complementary information about market dynamics across market conditions.
Mobeen Ur Rehman, Neeraj Nautiyal, Xuan Vinh Vo, Muhammad Kashif · 5 authors
Abstract Cryptocurrencies have regained mainstream attention, with Bitcoinx′s recent rally renewing investor interest across the digital asset space. This study focuses on the connectedness and spillover effects among seven major digital assets to examine the asymmetric relationships conditional on market conditions and time horizons. To emphasize the significance of short- and long-term trading dynamics, we explore the state dependence of linkages during extreme upward and downward market movements. Our findings suggest a significant connectedness induced by Litecoin and Ethereum. Short-term fluctuations are the dominant drivers of crypto-market vulnerability across quantiles and frequencies. Pronounced upper-quantile connectedness emerges consistently across all markets. Interestingly, major currencies, such as Bitcoin, Ethereum, Ripple, and Dash, act as receivers during upside and median market conditions, whereas Ethereum and Litecoin exhibit transmission effects. Moreover, no connectedness is detected between Ethereum and Bitcoin at extreme quantiles. The findings highlight the need for careful monitoring and risk assessment of extreme events, demanding careful risk monitoring during periods of turmoil.
This study examines the joint influence of environmental factors and U.S. financial markets on the returns of Bitcoin (BTC) and Ethereum (ETH), shedding light on sustainability-driven crypto valuation. The analysis integrates CO₂ emissions, green innovations, ESG scores and financial indicators, including the S&P 500, NASDAQ, Dow Jones, gold and oil prices, using monthly data from January 2019 to February 2025. A robust econometric framework is employed to assess both the long-term cointegration and the short-term sensitivities of BTC and ETH returns. The findings suggest that BTC exhibits a strong positive correlation with environmental innovations and ESG scores, indicating an alignment with investors focused on sustainability. In contrast, ETH exhibits weaker sensitivity to environmental factors despite its adoption of a more energy-efficient Proof-of-Stake mechanism. Both cryptocurrencies respond positively to gold and oil prices, reinforcing their potential as alternative hedging assets. By jointly evaluating environmental and financial drivers, this study contributes to the fields of sustainable finance and digital asset research, bridging the gap between ESG studies and cryptocurrency market analysis.
Enggar Sukma Kinanthi, Rosa De Lima Dyah Retno Palupi
Ketidakpastian pasar keuangan yang ditandai oleh meningkatnya volatilitas, guncangan global, dan perubahan perilaku investor mendorong perlunya evaluasi kembali peran berbagai aset dalam manajemen portofolio. Penelitian ini bertujuan untuk menganalisis dan mensintesis temuan empiris terkait peran saham, emas, dan Bitcoin dalam menghadapi ketidakpastian pasar keuangan. Analisis dilakukan menggunakan metode kajian literatur melalui perbandingan lintas aset untuk mengevaluasi kesesuaian antara prediksi teori keuangan klasik dengan temuan empiris pasar modern. Hasil kajian menunjukkan bahwa saham secara konsisten diklasifikasikan sebagai aset berisiko dengan volatilitas yang dipengaruhi oleh sentimen dan dinamika pasar, sementara emas relatif mempertahankan perannya sebagai aset lindung nilai meskipun efektivitasnya bersifat kondisional. Bitcoin, yang secara teoritis dipandang sebagai aset spekulatif berisiko tinggi, menunjukkan peran yang lebih kompleks dan kontekstual, berfungsi sebagai instrumen diversifikasi atau lindung nilai dalam kondisi pasar tertentu. Temuan ini menegaskan bahwa fungsi aset dalam portofolio modern tidak bersifat statis, melainkan dinamis dan dipengaruhi oleh ketidakpastian pasar serta perubahan perilaku investor.
Bitcoin, which was established in 2009, has turned into a worldwide cash. Bitcoin is a decentralized computerized money that isn't supported by any administration or national bank. It very well might be utilized to buy labour and products from retailers who acknowledge bitcoins. These bitcoins act as scrambled information lumps. This information is sent starting with one individual then onto the next, and the exchange is affirmed, i.e., cash is spent, requiring a lot of figuring ability to verify the singular exchanges precisely. The shared organization screens and ensures bitcoin moves between clients. It could be utilized to book inns, shop, do monetary exchanges, and even purchase computer games. The advancement of bitcoin digital money, the development of blockchain, and its utilization in certifiable substances are made sense of. This exploration paper will cover the ascent of Bitcoin in India
Open access
Blockchain Technology Applications and Security
Cyberloafing and Workplace Behavior
Innovations and Analysis in Business and Education
Rainer Stütz, Nicholas Stifter, Melitta Dragaschnig, Bernhard Haslhofer · 5 authors
It is well known that reusing cryptocurrency addresses undermines privacy. This also applies if the same addresses are used in different cryptocurrencies. Nevertheless, cross-chain address reuse appears to be a recurring phenomenon, especially in EVM-based designs. Previous works performed either direct address matching, or basic format conversion, to identify such cases. However, seemingly incompatible address formats e.g., in Bitcoin and Ethereum, can also be derived from the same public keys, since they rely on the same cryptographic primitives. In this paper, we therefore focus on the underlying public keys to discover reuse within, as well as across, different cryptocurrency networks, enabling us to also match incompatible address formats. Specifically, we analyze key reuse across Bitcoin, Ethereum, Litecoin, Dogecoin, Zcash and Tron. Our results reveal that cryptographic keys are extensively and actively reused across these networks, negatively impacting both privacy and security of their users. We are hence the first to expose and quantify cross-chain key reuse between UTXO and account-based cryptocurrencies. Moreover, we devise novel clustering methods across these different cryptocurrency networks that do not rely on heuristics and instead link entities by their knowledge of the underlying secret key.
Abstract. The Bitcoin blockchain is a distributed ledger of transactions maintained by a network of nodes. The protocol assumes that honest nodes control a majority of the network's computing power. Conventional wisdom suggests that a minority group cannot earn revenue disproportionate to its hashing power, implying that the rational strategy is to remain honest. However, Eyal and Sirer (2013) challenged this view by introducing "Selfish Mining," a strategy that enables a minority pool to earn rewards exceeding its share of computing power. This paper replicates the original study using Monte Carlo simulations to verify the threshold at which this attack becomes profitable. The results confirm that a pool controlling more than 1/3 of the network hashrate can theoretically achieve higher returns than honest mining.
This study explores the impact of Bitcoin on the Indonesian banking sector, emphasizing both the innovative opportunities and the challenges it presents. The research highlights Bitcoin's potential to enhance financial inclusion and drive technological growth while also identifying significant hurdles such as regulatory issues, security risks, and market volatility. Utilizing a mixed-methods approach, the study provides a nuanced analysis of Bitcoin's dual role as both a beneficial and threatening force within the financial landscape. It categorizes research variables into dependent, independent, and control groups to better understand their interactions and influence on traditional banking systems. The paper identifies a critical gap in existing literature regarding Bitcoin's specific effects on Indonesian banking operations, offering an empirical foundation for future research. The findings underscore the evolving regulatory frameworks and Bitcoin's complex role in the banking sector, highlighting the need for strategic management and careful regulation to harness its potential benefits while mitigating associated risks.
On September 7, 2021, El Salvador became the first country to adopt Bitcoin as its legal tender by establishing the “Bitcoin Law.” The Bitcoin Law is the first statute that describes its main objectives and endows Bitcoin with the status of a legal tender in El Salvador. Pursuant to the Bitcoin Law, El Salvador not only accepts Bitcoin as a means of payment methods for taxes and outstanding debts, but also requires all business enterprises to adopt Bitcoin as a medium of exchange for all commercial transactions. However, the soul of Bitcoin is not the state; instead, it belongs to a decentralized entity with incentives to maintain this currency. Therefore, the essence of Bitcoin is “a form of order without law.” A successful Bitcoin ecosystem would generate a mixture of law and nonlegal orders. In the midst of growing literature on digital currency, El Salvador offers a rare opportunity to understand the functions and limitations of Bitcoin as a legal tender in a monetary sovereignty.
Daniel Commey, Matilda Nkoom, Yousef Alsenani, Sena G. Hounsinou · 5 authors
Virtual Asset Service Providers (VASPs) face a fundamental tension between regulatory compliance and user privacy when detecting cross-institutional money laundering. Current approaches require either sharing sensitive transaction data or operating in isolation, leaving critical cross-chain laundering patterns undetected. We present FedGraph-VASP, a privacy-preserving federated graph learning framework that enables collaborative anti-money laundering (AML) without exposing raw user data. Our key contribution is a Boundary Embedding Exchange protocol that shares only compressed, non-invertible graph neural network representations of boundary accounts. These exchanges are secured using post-quantum cryptography, specifically the NIST-standardized Kyber-512 key encapsulation mechanism combined with AES-256-GCM authenticated encryption. Experiments on the Elliptic Bitcoin dataset with realistic Louvain partitioning show that FedGraph-VASP achieves an F1-score of 0.508, outperforming the state-of-the-art generative baseline FedSage+ (F1 = 0.453) by 12.1 percent on binary fraud detection. We further show robustness under low-connectivity settings where generative imputation degrades performance, while approaching centralized performance (F1 = 0.620) in high-connectivity regimes. We additionally evaluate generalization on an Ethereum fraud detection dataset, where FedGraph-VASP (F1 = 0.635) is less effective under sparse cross-silo connectivity, while FedSage+ excels (F1 = 0.855), outperforming even local training (F1 = 0.785). These results highlight a topology-dependent trade-off: embedding exchange benefits connected transaction graphs, whereas generative imputation can dominate in highly modular sparse graphs. A privacy audit shows embeddings are only partially invertible (R^2 = 0.32), limiting exact feature recovery.
This study examines the dynamic and multiscale connectedness among cryptocurrencies, energy markets, macro-financial variables, and environmental indicators in the United States from January 2014 to June 2025. Using a hybrid framework that combines wavelet decomposition with a time-varying parameter vector autoregression (TVP-VAR), we assess spillovers across short-, medium-, and long-term horizons. The results reveal a persistently high level of systemic integration, with the Total Connectedness Index (TCI) ranging between 70 % and 90 % and reaching about 93 % at long horizons. Three contagion regimes are identified: energy-crypto dominance before 2020, financial synchronization during the COVID-19 crisis, and a macro-energy-environmental phase after 2021 that evolves into a digital-sustainability regime by 2025. The multiscale decomposition uncovers hidden directional reversals, Bitcoin price shifts from a short-term volatility transmitter to a long-run structural influencer, while transaction and capitalization variables move from emitters to receivers as horizons lengthen. Robustness tests using a rolling-window VAR confirm the persistence of these dynamics. Overall, the evidence shows that short-term contagion is speculative and energy-driven, whereas long-term connectedness is anchored in inflation, industrial production, and electricity prices. These findings offer actionable insights for investors and policymakers seeking to manage systemic risk and design sustainable strategies at the intersection of digital finance, energy markets, and environmental policy.
For the past three decades, the architecture of the internet has rested on two primary pillars - communication on the World Wide Web and Value such as Bitcoin/Distributed ledgers. However, a third critical pillar, Private Coordination has remained dependent on centralised intermediaries, effectively creating a surveillance architecture by default. This paper introduces the 'Stateless Pattern', a novel network topology that replaces the traditional 'Fortress' security model (database-centric) with a 'Mist' model (ephemeral relays). By utilising client-side cryptography and self-destructing server instances, we demonstrate a protocol where the server acts as a blind medium rather than a custodian of state. We present empirical data from a live deployment (https://signingroom.io), analysing over 1,900 requests and cache-hit ratios to validate the system's 'Zero-Knowledge' properties and institutional utility. The findings suggest that digital privacy can be commoditised as a utility, technically enforcing specific articles of the universal declaration of human rights not through policy, but through physics.
Abstract This article examines how bitcoin has acquired religious significance among many techno-libertarians, who hold it as a symbol promising deliverance from a fallen world. Drawing on both participant observation at bitcoin meetups and the 2023 Bitcoin Conference, as well as digital ethnography on X, the article presents a thick description of how bitcoiners construct specific beliefs about the world and their place in it, as well as ritual practices that vivify these beliefs and sanctify those who hold them. These beliefs and practices constitute bitcoin, in turn, as a distinct moral community in which bitcoin is symbolized as an instrument of salvation from a failing institutional order. This Durkheimian analysis contributes to understanding how money in modern society carries with it religious meanings about the world and human history. And it also contributes to an understanding of the specific ideological formation driving techno-libertarianism as an ascendant political interest today.
Eclipse attacks isolate blockchain nodes by monopolizing their peer-to-peer connections. The attacks were extensively studied in Bitcoin (SP'15, SP'20, CCS'21, SP'23) and Monero (NDSS'25), but their practicality against Ethereum nodes remains underexplored, particularly in the post-Merge settings. We present the first end-to-end implementation of an eclipse attack targeting Ethereum (2.0 version) execution-layer nodes. Our attack exploits the bootstrapping and peer management logic of Ethereum to fully isolate a node upon restart. We introduce a multi-stage strategy that majorly includes (i) poisoning the node's discovery table via unsolicited messages, (ii) infiltrating Ethereum's DNS-based peerlist by identifying and manipulating the official DNS crawler, and (iii) hijacking idle incoming connection slots across the network to block benign connections. Our DNS list poisoning is the first in the cryptocurrency context and requires only 28 IP addresses over 100 days. Slots hijacking raises outgoing redirection success from 45\% to 95\%. We validate our approach through controlled experiments on Ethereum's Sepolia testnet and broad measurements on the mainnet. Our findings demonstrate that over 80\% of public nodes do not leave sufficient idle capacity for effective slots occupation, highlighting the feasibility and severity of the threat. We further propose concrete countermeasures and responsibly disclosed all findings to Ethereum's security team.