Nourhaine Nefzi, A. Melki, Sahar Loukil, Ahmed Jeribi
Abstract This study investigates the dynamic connectedness within the cryptocurrency market by analyzing four distinct cryptomarket blocks: Bitcoin and Ethereum (conventional cryptocurrencies); PAXG, DGX, and GLC (gold-backed cryptocurrencies); LINK and MNK (decentralized finance); and THETA and MANA (nonfungible tokens). Using the time-varying parameter quantile vector autoregressive (TVP-Quantile VAR) model for the period 2019–2023, our analysis reveals significant insights into the risk transmission dynamics among cryptocurrencies. Both conventional cryptocurrencies exhibit a consistent net transmitter effect in extreme periods, whereas decentralized finance (DeFi) and nonfungible tokens (NFTs) shift between a net shock transmitter and a net shock receiver over time and quantiles. Moreover, our results shed light on the hedging and safe haven properties of these assets. By linking the dynamic connectedness findings with established literature on hedging and safe haven functions, we elucidate how these cryptocurrencies perform under varying market conditions. Specifically, we report that the role of LINK, MNK, THETA, and MANA as reliable safe-haven assets is contingent upon the observed period. We also observe the hedge and safe haven properties of selected gold-backed cryptocurrencies within the network. Overall, our findings suggest that, despite the dynamic connectedness of the cryptocurrency market, investors have the flexibility to diversify across these digital assets.
Unlike Ethereum, which was conceived as a general-purpose smart-contract platform, Bitcoin was designed primarily as a transaction ledger for its native currency, which limits programmability for conditional applications. This constraint is particularly evident when considering oracles, mechanisms that enable Bitcoin contracts to depend on exogenous events. This paper investigates whether new oracle designs have emerged for Bitcoin Layer 1 since the 2015 transition to the Ethereum smart contracts era and whether subsequent Bitcoin improvement proposals have expanded oracles' implementability. Using Scopus and Web of Science searches, complemented by Google Scholar to capture protocol proposals, we observe that the indexed academic coverage remains limited, and many contributions circulate outside journal venues. Within the retrieved corpus, the main post-2015 shift is from multisig-style, which envisioned oracles as co-signers, toward attestation-based designs, mainly represented by Discreet Log Contracts (DLCs), which show stronger Bitcoin community compliance, tool support, and evidence of practical implementations in real-world scenarios such as betting and prediction-market mechanisms.
This work presents a concept and implementation for the secure storage and transfer of quality-relevant data of milled workpieces from online-quality assurance processes enabled by real-time simulation models. It utilises Non-Fungible Tokens (NFT) to securely and interoperably store quality data in the form of an Asset Administration Shell (AAS) on a public Ethereum blockchain. Minted by a custom smart contract, the NFTs reference the metadata saved in the Interplanetary File System (IPFS), allowing new data from additional processing steps to be added in a flexible yet secure manner. The concept enables automated traceability throughout the value chain, minimising the need for time-consuming and costly repetitive manual quality checks.
Open access
3 source records
Digital Transformation in Industry
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
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.
Multi-implementation systems are increasingly audited against natural-language specifications. Differential testing scales well when implementations disagree, but it provides little signal when all implementations converge on the same incorrect interpretation of an ambiguous requirement. We present SPECA, a Specification-to-Checklist Auditing framework that turns normative requirements into checklists, maps them to implementation locations, and supports cross-implementation reuse. We instantiate SPECA in an in-the-wild security audit contest for the Ethereum Fusaka upgrade, covering 11 production clients. Across 54 submissions, 17 were judged valid by the contest organizers. Cross-implementation checks account for 76.5 percent (13 of 17) of valid findings, suggesting that checklist-derived one-to-many reuse is a practical scaling mechanism in multi-implementation audits. To understand false positives, we manually coded the 37 invalid submissions and find that threat model misalignment explains 56.8 percent (21 of 37): reports that rely on assumptions about trust boundaries or scope that contradict the audit's rules. We detected no High or Medium findings in the V1 deployment; misses concentrated in specification details and implicit assumptions (57.1 percent), timing and concurrency issues (28.6 percent), and external library dependencies (14.3 percent). Our improved agent, evaluated against the ground truth of a competitive audit, achieved a strict recall of 27.3 percent on high-impact vulnerabilities, placing it in the top 4 percent of human auditors and outperforming 49 of 51 contestants on critical issues. These results, though from a single deployment, suggest that early, explicit threat modeling is essential for reducing false positives and focusing agentic auditing effort. The agent-driven process enables expert validation and submission in about 40 minutes on average.
This study examines the pricing dynamics of Non-Fungible Tokens (NFTs) in the secondary market using advanced machine-learning techniques. We construct a large dataset of Ethereum-based NFT transactions initially comprising over 500,000 raw blockchain observations spanning multiple NFT segments, including art, collectibles, gaming, metaverse, and utility assets, over the period from November 2018 to March 2023. Following data preprocessing, synchronization across data sources, and the construction of history-dependent features, the analysis focuses on a final analytical sample of approximately 70,000 transactions. To address the challenges of non-fungibility, thin trading, and high price dispersion, we develop an interpretable predictive framework that integrates domain-informed manual feature engineering, automated Deep Feature Synthesis, and dimensionality reduction via Principal Component Analysis. Three non-linear models—Random Forest, XGBoost, and a Multilayer Perceptron—are trained and evaluated using both random and time-aware validation strategies. The results indicate that XGBoost consistently achieves the highest predictive accuracy, both overall and across individual NFT segments, while historical transaction prices emerge as the dominant predictor of future prices. Segment-level analysis reveals substantial heterogeneity in predictability, with art and collectible NFTs exhibiting more stable pricing patterns than gaming and metaverse assets. Overall, the findings highlight strong path dependence and reputation-driven valuation in NFT markets and demonstrate that carefully designed machine-learning models can deliver high predictive performance without sacrificing economic interpretability.
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.
Zeta Avarikioti, Ray Neiheiser, Krzysztof Pietrzak, Michelle Yeo
Over the last years, Ethereum has evolved into a public platform that safeguards the savings of hundreds of millions of people and secures more than $650 billion in assets, placing it among the top 25 stock exchanges worldwide in market capitalization, ahead of Singapore, Mexico, and Thailand. As such, the performance and security of the Ethereum blockchain are not only of theoretical interest, but also carry significant global economic implications. At the time of writing, the Ethereum platform is collectively secured by almost one million validators highlighting its decentralized nature and underlining its economic security guarantees. However, due to this large validator set, the protocol takes around 15 minutes to finalize a block which is prohibitively slow for many real world applications. This delay is largely driven by the cost of aggregating and disseminating signatures across a validator set of this scale. Furthermore, as we show in this paper, the existing protocol that is used to aggregate and disseminate the signatures has several shortcomings that can be exploited by adversaries to shift stake proportion from honest to adversarial nodes. In this paper, we introduce Wonderboom, the first million scale aggregation protocol that can efficiently aggregate the signatures of millions of validators in a single Ethereum slot (x32 faster) while offering higher security guarantees than the state of the art protocol used in Ethereum. Furthermore, to evaluate Wonderboom, we implement the first simulation tool that can simulate such a protocol on the million scale and show that even in the worst case Wonderboom can aggregate and verify more than 2 million signatures within a single Ethereum slot.
Modern passport systems face significant challenges in secure data sharing, real-time verification, and user-controlled authorization, particularly in cross-border scenarios. Existing digital passport solutions, often built on permissioned blockchains, suffer from limited transparency, scalability, and high operational costs. This paper proposes a decentralized passport management system based on an Ethereum Layer 2 architecture that combines global governance with high-throughput and cost-efficient passport operations. The system adopts a hybrid design in which a Global Passport Registry smart contract is deployed on the Ethereum mainnet for cross-country coordination, while passport issuance, access control, and identity management are handled on Layer 2 networks through country-operated Passport Managers and user-specific Personal Passport smart contracts. Extensive performance evaluations show that Ethereum Layer 1 throughput saturates at approximately 40–50 transactions per second (TPS), whereas the proposed Layer 2 deployment consistently exceeds 150 TPS and reaches up to 300 TPS under higher-performance environments, significantly surpassing the estimated system requirement of 70 TPS. These improvements result in faster response times, reduced congestion, and substantially lower transaction costs, demonstrating that public Ethereum Layer 2 infrastructures can effectively support a scalable, self-sovereign, privacy-preserving, and globally verifiable digital passport system suitable for real-world deployment.
Abstract Ensuring the security of smart contracts is essential for maintaining the reliability and trustworthiness of decentralized applications, which are deployed across various domains, including industrial applications. In pursuit of this goal, it is imperative to analyze the common errors developers make when crafting smart contracts on the infrastructure that gave birth to them, i.e., the Ethereum blockchain. In this paper, we present a comprehensive analysis of the vulnerabilities in Ethereum smart contracts. Our methodology involves downloading the entire Ethereum blockchain and identifying smart contracts, which we then scan for vulnerabilities using various tools. We have discovered numerous vulnerabilities across many deployed smart contracts, highlighting the need for improved development practices. This analysis provides critical insights into the prevalence of security issues and underscores the urgency of raising development standards. By promoting the adoption of secure-by-design principles, our research seeks to enhance security standards within the Ethereum smart contract ecosystem.
Multi-chain deployment has become a mainstream strategy for U.S.-based DAOs, yet treasury management faces three core bottlenecks: cross-chain liquidity fragmentation, inadequate compliance with U.S. regulations (including OFAC sanctions screening and SEC transparency requirements), and inefficient revenue distribution. Leveraging the incubation practices of over 12 U.S. DAOs (via daos.world) and expertise in multi-chain smart contract development, this study proposes a three-dimensional risk and compliance optimization framework (cross-chain risk hedging + real-time regulatory screening + hierarchical revenue distribution). Empirical testing on 8 U.S. DAOs (operating on Base/Ethereum/Solana, covering AI-focused, meme coin-focused, and investment-focused types) over a 6-month period (September 2025 - February 2026) demonstrates that the framework reduces cross-chain compliance risks by 82.3% (OFAC violation rate drops from 18.0% to 3.2%), increases the annualized treasury return rate by 17.6% (from 4.2% to 5.04%), lowers cross-chain transaction costs by 28.5% (average Gas fee decreases from $12.8 to $9.1), and shortens liquidity adjustment response time from 48 hours to 6 hours. Integrating U.S. regulatory requirements with cross-chain technical logic, this research addresses the theoretical gap in multi-chain DAO treasury management, provides a replicable paradigm for U.S. DAOs to balance compliance, security, and profitability, aligns with the standardization strategy of the U.S. Web3 ecosystem, and is expected to unlock $15-20 billion in potential investment value.
Термин сферы децентрализованных финансов анализируется в рамках когнитивной парадигмы. Целью исследования является определение роли когнитивно-матричного анализа в контексте изучения терминов рассматриваемой области знания. Объектом исследования выступает термин “decentralized finance”. Предметом является применение когнитивно-матричного анализа как метода изучения терминолексики сферы децентрализованных финансов. Научная новизна исследования заключается в том, что впервые в отечественном терминоведении проводится изучение англоязычных терминов указанной сферы с когнитивной позиции. В частности, приводится пример использования когнитивно-матричного анализа для определения концептуальной структуры термина изучаемой области знания. В статье рассматривается несколько подходов к определению понятия «термин»: субстанциональный, функциональный и когнитивный. Проводится когнитивно-матричный анализ на материале термина “decentralized finance” и его определений, закрепленных в глоссариях децентрализованных платформ, приложений и новостных англоязычных интернет-ресурсов, таких как Binance Academy, Consensys, Ethereum Website, Ethereum Glossary и Tastycrypto. В результате анализа определено, что наибольшую компонентную представленность в структуре концепта DECENTRALIZED FINANCE демонстрируют «техническая и технологическая» и «социальная» области, в то время как «финансовая» и «правовая» репрезентированы менее широко, что обусловлено смещением акцента в определениях термина с базовых характеристик на инновационные и дифференцирующие. Когнитивно-матричный анализ позволяет выявлять периферийные области и концептуальные компоненты когнитивной структуры терминов сферы децентрализованных финансов, подчеркивая их междисциплинарный характер. The term “decentralized finance” is analyzed within the framework of the cognitive paradigm. The article examinesthe application of cognitive-matrix analysis as a method for studying the terminological vocabulary of the specified domain. The object of the research is the term “decentralized finance”, while the subject is the application of cognitive matrix analysis as a method for studying the terminological vocabulary of decentralized finance. The novelty of the research lies in the fact that, for the first time in Russian terminology studies, English-language terms of the specified field are examined from a cognitive perspective. An example is provided of how cognitive matrix analysis can be used to identify the conceptual structure of decentralized finance terms. The article considers several approaches to defining the concept of the term: the substantial, functional, and cognitive. A cognitive matrix analysis is conducted on the material of the term “decentralized finance”, as represented in the glossaries of decentralized platforms, applications, and English-language news resources such as Binance Academy, Consensys, Ethereum Website, Ethereum Glossary, and Tastycrypto. The analysis reveals that the “technical and technological” and “social” peripheral domains are most prominently represented in the structure of the concept DECENTRALIZED FINANCE, whereas the “financial” and “legal” domains are less explicitly present. This is due to the shift in focus from basic characteristics of the concept to innovative and differentiating features in the term’s definitions. Cognitive matrix analysis makes it possible to identify peripheral domains and conceptual components of the cognitive structure of DeFi terminological vocabulary, highlighting its interdisciplinary nature.
Aqsa Rashid, Raja Wasim Ahmad, Mirna Nachouki, Atta Ur Rehman Khan
Ensuring food safety and traceability in fruit supply chains (FSC) remains a critical concern, as traditional centralized methods often suffer from data manipulation, lack of transparency, and delayed responses during contamination events. These challenges lead to reduced consumer trust and inefficiencies in monitoring product integrity throughout the supply network. To address these limitations, this paper presents a blockchain-based framework that leverages cryptographic protocols and smart contracts to secure, automate, and validate traceability processes across all stages of the fruit supply chain. The proposed FSC_SDG system enforces trusted data recording, real-time provenance verification, and autonomous policy execution, while aligning with the United Nations Sustainable Development Goals (UN-SDGs). A proof-of-concept prototype was implemented on the Ethereum blockchain to assess performance. Experimental evaluations demonstrate reduced latency in traceability verification, improved data integrity, and enhanced resistance to tampering compared with existing approaches. These results confirm the effectiveness of the proposed framework in strengthening food safety, transparency, and trust within fruit supply chains.
Block space on the blockchain is scarce and must be allocated efficiently through block building. However, Ethereum's current block-building ecosystem, MEV-Boost, has become highly centralized due to integration, which distorts competition, reduces blockspace efficiency, and obscures MEV flow transparency. To guarantee equitability and economic efficiency in block building, we propose $\mathrm{Boost+}$, a system that decouples the process into collecting and ordering transactions, and ensures equal access to all collected transactions. The core of $\mathrm{Boost+}$ is the mechanism $\mathit{M}_{\mathrm{Boost+}}$, built around a default algorithm. $\mathit{M}_{\mathrm{Boost+}}$ aligns incentives for both searchers (intermediaries that generate or route transactions) and builders: Truthful bidding is a dominant strategy for all builders. For searchers, truthful reporting is dominant whenever the default algorithm dominates competing builders, and it remains dominant for all conflict-free transactions, even when builders may win. We further show that even if a searcher can technically integrate with a builder, non-integration combined with truthful bidding still dominates any deviation for conflict-free transactions. We also implement a concrete default algorithm informed by empirical analysis of real-world transactions and evaluate its efficacy using historical transaction data.
Arivarasan Karmegam, Lucianna Kiffer, Antonio Fernández Anta
Blockchain validators can reduce block processing time by exploiting multi-core CPUs, but deterministic execution must preserve a given total order while respecting transaction conflicts and per-block runtime limits. This paper systematically examines how validators can exploit multi-core parallelism during both block construction and execution without violating blockchain semantics. We formalize two validator-side optimization problems: (i) executing an already ordered block on \(p\) cores to minimize makespan while ensuring equivalence to sequential execution; and (ii) selecting and scheduling a subset of mempool transactions under a runtime limit \(B\) to maximize validator reward. For both, we develop exact Mixed-Integer Linear Programming (MILP) formulations that capture conflict, order, and capacity constraints, and propose fast deterministic heuristics that scale to realistic workloads. Using Ethereum mainnet traces and including a Solana-inspired declared-access baseline (Sol) for ordered-block scheduling and a simple reward-greedy baseline (RG) for block construction, we empirically quantify the trade-offs between optimality and runtime.
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
Personal Health Records (PHRs) enable personalized and continuous healthcare services, but contain highly sensitive information, requiring strong security and privacy safeguards. Self-sovereign architectures, where individuals retain full control over their data, represent a promising model for secure PHR sharing. In our prior work, we implemented a blockchain-based system using Non-Fungible Tokens (NFTs) to represent data ownership and usage rights. While NFTs provide tamper resistance, NFT-only access control is vulnerable to wallet compromise and requires explicit user consent, making it unsuitable for emergency access when patients are unconscious or otherwise unable to consent. To address these limitations, we newly propose a hybrid PHR-sharing framework combining NFTs with Attribute-Based Encryption (ABE). Our new approach enforces cryptographic access policies beyond NFT possession and enables emergency access to predefined medical information without explicit user consent. We analyze representative attack scenarios and show that the scheme provides secure access control and rights management. We implement a prototype and evaluate its performance. For 1 MB of data, used as a practical upper bound for text-based PHR records based on wearable-device measurements, retrieval takes approximately 1 second, while registration and access granting take approximately 12 and 6 seconds on the Base testnet, a high-speed Ethereum-compatible test network. These results demonstrate practical feasibility, with further optimization possible through faster blockchain networks or reduced blockchain transactions.
R. N. V. Jagan Mohan, Pravallika Sree Rayanoothala, R. Praneetha Sree
Agriculture faces multifaceted challenges including climate variability, soil degradation, and supply chain inefficiencies, particularly for smallholder farmers practicing multicropping. This study systematically integrates blockchain technology for secure, transparent transactions with reinforcement learning (RL)-optimized Neutrosophic multi-regression for precise crop loss prediction in multicropping systems. Using real-world data from six crops (rice, banana, turmeric, elephant foot yam, coconut, cocoa), Neutrosophic multi-regression estimated losses with RL hyperparameter tuning, achieving superior prediction accuracy. A blockchain framework was developed for farmer validation, transaction security, and smart contract execution using Ethereum/Ganache. Results demonstrate 25%–35% reduction in predicted crop losses and enhanced supply chain traceability. This Smart Agriculture 5.0 framework advances Agriculture 4.0 through human-AI symbiosis and uncertainty modeling, addressing single-point failures, data privacy, and trust deficits for scalable sustainable farming Through this multidimensional approach, the study endeavors to not only enhance the productivity and sustainability of agricultural practices but also to foster resilience in the face of evolving challenges.
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.
Do online narratives leave a measurable imprint on prices in markets for digital or cultural goods? This paper evaluates how community attention and sentiment relate to valuation in major Ethereum NFT collections after accounting for time effects, market-wide conditions, and persistent visual heterogeneity. Transaction data for large generative collections are merged with Reddit-based discourse measures available for 25 collections, covering 87{,}696 secondary-market sales from January 2021 through March 2025. Visual differences are absorbed by a transparent, within-collection standardized index built from explicit image traits and aggregated via PCA. Discourse is summarized at the collection-by-bin level using discussion intensity and lexicon-based tone measures, with smoothing to reduce noise when text volume is sparse. A mixed-effects specification with a Mundlak within--between decomposition separates persistent cross-collection differences from within-collection fluctuations. Valuations align most strongly with sustained collection-level attention and sentiment environments; within collections, short-horizon negativity is consistently associated with higher prices, and attention is most informative when measured as cumulative engagement over multiple prior windows.
Open access
3 source records
econ.GN
Consumer Behavior in Brand Consumption and Identification
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.
Abdullah Ayub Khan, Abdullah M. Baqasah, Majed Alsafyani, Hamed Alsufyani · 6 authors
The revolution in Blockchain Distributed Ledger Technology (BDLT) is changing conventional structures and creating previously unattainable opportunities across a variety of industrial fields. This study explores new developments, opportunities, and trends while tackling important issues that highlight the revolutionary potential of BDLT. For secure, automated, and dependable ecosystem management, it focuses on innovations like Denaturalized Finance (Defi), chaincode, and BDLT interface with the Internet of Things (IoT). The investigation of hybrid blockchain models, which combine the benefits of private and public blockchains, is a novel component of this research. It provides a customized strategy to guarantee improved scalability, privacy, and performance. Conversely, this study highlighted the critical function of Hyperledger, a modular framework that makes enterprise-level blockchain solutions possible. Thus, Ethereum is a flexible platform with strong chaincode capabilities that facilitate the creation of Distributed Applications (DApps). Such opportunities for advancements are evaluated closely in order to demonstrate how they contribute to practical uses and innovations unique to a given sector. To improve worldwide acceptance, the paper also presents Systematic Literature Review (SLR) in order to demonstrate the existing innovative frameworks, especially Hyperledger Technology (HT) for resolving constraints such as consensus protocols for energy efficiency and adaptive regulatory models. For technological experts, industrial developers, and third-party policymakers seeking to harness BDLT's disruptive capabilities while navigating its complexity, this paper offers new viewpoints and practical insights to help close the gap between theoretical innovation and real-world applications.
Ethereum-Smart Contracts verwalten häufig erhebliche finanzielle Werte. Da sie praktisch unveränderlich sind und häufig böswilligen Akteuren ausgesetzt sind, die durch finanziellen Gewinn motiviert sind, stellt die semantische Korrektheit eine zentrale Sicherheitsanforderung dar. Etablierte Testmethoden reichen oft nicht aus, um die Korrektheit über alle möglichen Ausführungspfade hinweg zu gewährleisten. Daher stellt die formale Verifikation ein wesentliches Mittel dar, um solche Sicherheitsgarantien zu stärken. Diese Arbeit untersucht die auf symbolischer Ausführung basierende Verifikation von Ethereum-Smart-Contracts unter Verwendung des KEVM-Frameworks sowie zweier darauf aufbauender Werkzeuge auf höherer Abstraktionsebene: ACT und Kontrol. Diese Arbeit behandelt Fragestellungen hinsichtlich der Ausdrucksstärke und Konstruktion von Beweisen sowie der Nutzbarkeit und Interpretierbarkeit sowohl von Beweisdefinitionen als auch von generierten Beweisartefakten. Es wird untersucht, ob und welche praktischen Herausforderungen bei der Verwendung von KEVM und zugehörigen Werkzeugen auftreten, einschließlich der Syntax, der verfügbaren Debugging-Werkzeuge sowie der Analyse von Beweisen und Gegenbeweisen. Anschließend erfolgt eine Evaluierung, wie semantische Eigenschaften über alle Werkzeuge hinweg spezifiziert werden können und wie präzise diese spezifiziert werden, wobei insbesondere die Zielkonflikte zwischen unterschiedlichen Abstraktionsebenen hervorgehoben werden. Darüber hinaus verifizieren wir semantische Eigenschaften von ERC20-Token-Smart-Contracts mit besonderem Fokus darauf, ob bestimmte Einträge in der Common Vulnerabilities and Exposures (CVE)-Datenbank tatsächlich korrekt sind oder mithilfe von KEVM widerlegt werden können. Zu diesem Zweck analysieren wir die gemeldete Schwachstelle, formulieren ein formales Argument gegen die behauptete Verletzung und konstruieren darauf aufbauend einen Beweis unter Verwendung von Kontrol. Dabei zeigen wir, wie semantische Eigenschaften innerhalb des Frameworks formuliert und verifiziert werden können. Abschließend untersuchen wir die Community-Aktivität rund um KEVM und dessen Ökosystem. Dazu werden GitHub-Repository-Metriken sowie Kommunikationsdaten aus Discord ausgewertet, um Entwicklungsaktivität, Dynamiken der Beitragenden sowie Muster im Nutzer-Support zu analysieren. Diese kombinierte Perspektive aus technischer und empirischer Sicht liefert eine ganzheitliche Betrachtung von KEVM sowohl als formales Verifikationsframework als auch als Entwickler-Ökosystem.
Weihong Wang, Yana Dimova, Victor Vansteenkiste, Tom Van Goethem · 5 authors
Cryptocurrency wallets are the primary interface for managing pseudonymous blockchain addresses, viewing balances, and interacting with Web3 applications. Although users typically assume that their addresses remain independent of each other unless intentionally revealed, modern wallets routinely communicate with both blockchain infrastructure and decentralized applications (dApps), generating network-side and web-side signals that may undermine this assumption. In this paper, we identify and formalize five privacy threats that arise directly from wallets interacting with the network and the web browser. Using large-scale dynamic measurements of 85 of the most popular Chrome Web Store browser-extension wallets (representing 35.16 million users), we observe that routine remote procedure call (RPC) operations leak structural links between a user's addresses; that the majority of Ethereum wallets implement permission revocation inconsistently and continue to expose previously revoked addresses across sessions; and that many wallets inject their provider interfaces into cross-origin iframes, enabling passive cross-site tracking beyond dApps and potentially real-world identity deanonymization without user interaction. Taken together, our results show that these wallet behaviors leak sensitive information that can be used to link multiple addresses to the same user, track wallet users across sessions and sites, and connect their browsing activity to their on-chain wealth. We discuss practical mitigations and show that many of these threats can be substantially reduced through improved wallet implementation, stronger privacy considerations in ecosystem standards, and stricter controls over provider exposure. Our results highlight the need for standardized, privacy-preserving wallet architectures and provide actionable guidance for strengthening user privacy in the emerging Web3 ecosystem.