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51,074 results · page 170 of 2,129
Shehzad Ahmed, Rafiqul Bhuyan, Rubaiyat Islam
No abstract is available for this record.
N K Vasilieva, J. D. Darmilova, А.П. ГОРБАТКО, A. N. Kalinichenko
This article examines the concept of cryptocurrency and its specific features. Based on the collection and analysis of information, the paper identifies the dual nature of cryptocurrency, which manifests itself both in the provision of new financial opportunities and in the expansion of corruption and fraudulent schemes. The article explores legal measures and approaches to combating cryptocurrency-related offenses, as well as current methods of detecting corruption involving cryptocurrencies.
Ba Chu, Ilias Tsiakas
No abstract is available for this record.
Michael Neubert, Wolfgang Rams, Patrick Gruhn, Marcel Lötscher
No abstract is available for this record.
Ashley Card, Diego Marmsoler
Smart contracts deployed on the Ethereum blockchain execute on the Ethereum Virtual Machine (EVM) and handle financial operations such as payments, asset transfers, and auctions. Given the high value they control, correctness in these contracts is critical, as errors and vulnerabilities have led to losses totalling hundreds of millions of dollars. To address this problem, we develop a novel formalization of the EVM. Compared to existing formalizations, our formalization is in Isabelle/HOL, covers all current EVM opcodes, and formalizes cross-contract execution. Thus, it allows us to express properties which are out of scope for other formalizations. To allow for the execution of our formalization, we implement a code generator, allowing it to be exported as a stand-alone Haskell program. We then validate the semantics by executing νmprint{25000} test cases from the official Ethereum test suite. Our formalization can be used to verify concrete smart contracts but also to reason about the correctness of tools and techniques which manipulate bytecode, such as compilers or optimizers.
Koresh Galil
No abstract is available for this record.
David Krause
No abstract is available for this record.
David Krause
No abstract is available for this record.
Craig S Wright
No abstract is available for this record.
Aurélien Perez
No abstract is available for this record.
Muhammad Noraiz Abid
No abstract is available for this record.
Vikram Dham
No abstract is available for this record.
Michael Fiolka, Tobias Jornitz, Luisa Strehl
Since the emergence of the blockchain and the uprising of ChatGPT, the Distributed Ledger Technology (DLT) and Artificial Intelligence (AI) are well-discussed topics both in public and professional circles, but especially in the domain of Supply Chain Management (SCM). These subjects are tech-savvy, complicated to explain and even more complex to use. On top of that, there is a scientific discussion around synergies in combining both technologies. Together they can be useful in engaging current challenges in SCM, where transparency-related data has to be generated, processed and formed into decisions and reports. To investigate the potentials of these technologies working together in a non-financial reporting environment, we performed a systematic literature review. We also included literature focusing solely on the technological perspective. The objective is a comprehensive overview on how a combination of DLT and AI could help to solve current challenges arising from sustainability related regulations. Further, we discussed ideas around Internet of Things applications or Federated Learning approaches, that use data from different entities and can be used in sustainability reporting, exploring possibilities to enhance compliance and responsible business conduct in SCM.
J. D. C. Vergara, D. E. Burdin, R.H. Davletbaev, Д. К. Д. Вергара · 6 authors
In the context of the digitalization of the economy, the problem of organizing effective document management in the non-profit sector has become particularly pressing. Traditional methods of managing information flows struggle to fully adapt to the requirements of transparency, accountability, and the legal significance of data. This article proposes a methodological approach to solving the document management problem based on the integration of distributed ledger technologies and smart contracts. A conceptual model of digital document management has been developed, in which each business event is represented as a smart document with legal verification in a blockchain environment. The paper describes in detail the stages of architecture development, the algorithms for interaction between participants, and the mechanisms for ensuring the immutability of records. The obtained results make it possible to increase transparency and trust between participants in non-profit organizations, ensure the automation of legally significant transactions, and minimize the risk of data falsification. The practical significance lies in the possibility of implementing the proposed approach into existing management systems of non-profit structures, which creates the basis for the formation of digital ecosystems of trusted document management.
R. Brian Langrin
No abstract is available for this record.
Ken Alabi
No abstract is available for this record.
Francis Chigozie Emmanuel, Ogaziechi Tobechi Anold, Obidinma Christian Alozie, Ikenna Tonna Adiele
The global freelance economy has experienced rapid growth, yet existing payment and escrow systems remain constrained by structural inefficiencies inherent in both centralized fiat-based and decentralized cryptocurrency-based models. Centralized escrow systems, while widely adopted due to their regulatory compliance and usability, suffer from custodial opacity, information asymmetry, high transaction costs, and limited verifiability. Conversely, purely decentralized blockchain-based escrow systems offer transparency and trust-minimized execution through smart contracts but face barriers including cryptocurrency price volatility, limited fiat integration, steep technical learning curves, and inadequate dispute resolution mechanisms for subjective deliverables. This article, a hybrid escrow system integrates traditional fiat payment infrastructure with decentralized Ethereum-compatible smart contract execution. The system adopts a three-layer architecture comprising a centralized service layer, a middleware synchronization layer, and a decentralized execution layer. A Finite State Machine (FSM) model governs escrow state transitions across both fiat-funded and cryptocurrency-funded transactions, ensuring determinism, auditability, and consistency. The system further incorporates a human-in-the-loop dispute resolution framework anchored to blockchain execution, enabling fair and transparent adjudication of subjective conflicts. Evaluation results demonstrate that the proposed hybrid architecture successfully bridges the gap between traditional finance and decentralized systems. The system achieved 100% correct FSM state enforcement with zero unauthorized fund releases across all test scenarios. Fiat-funded contracts were synchronized to the blockchain with an average latency of 8.4 seconds, while cryptocurrency-funded contracts confirmed on-chain within a median of 3.2 seconds on the Polygon testnet. All three dispute resolution outcomes were correctly enforced on-chain within an average of 5.1 seconds following adjudication, and API response times remained below 420 milliseconds under concurrent user loads. An ablation study further confirmed that all three architectural layers are individually necessary, as removing any single layer degraded transparency, payment flexibility, dispute resolution capability, or user accessibility. This research contributes a scalable and adaptable hybrid escrow blueprint applicable to fintech development, digital labour platforms, and cross-border payment systems.
Guillaume Andrieu
No abstract is available for this record.
Deepak Ranjan Sahoo, Vaishali Deepak Sahoo
This paper presents a comprehensive structural analysis of cryptocurrency derivative markets spanning January 2019 to December 2024, covering Bitcoin (BTC), Ethereum (ETH), and six additional tokens across over 2.83 billion high-frequency transactions on eight major centralized exchanges and three decentralized finance (DeFi) derivative protocols. Using a theoretically grounded multi-method framework—comprising Vector Error Correction Models (VECM), Hasbrouck (1995) and Gonzalo-Granger (1995) information share decompositions, Heston (1993) and rough volatility (Gatheral et al., 2018) stochastic models, DCC-GARCH(1,1) augmented with realized kernel estimators, MIDAS regressions linking high-frequency derivative signals to lowerfrequency on-chain variables, and panel quantile regressions for cross-sectional volatility risk—we deliver six primary empirical contributions. First, perpetual swap markets consistently dominate spot markets in price discovery, contributing 63.4% (BTC) and 58.7% (ETH) of price-efficient information on average, rising to 72.1% and 68.4%, respectively, during the top quartile of volatility days—consistent with informed-agent migration to leveraged venues. Second, the Heston leverage correlation estimate ρ = −0.61 for BTC and ρ = −0.73 for ETH reflects asymmetric tail risk demand rather than balance-sheet leverage, with the implied volatility smirk's left-tail slope strongly cointegrated with funding-rate deviations (r = −0.54, p < 0.001). Third, we estimate a time-varying variance risk premium averaging 14.8 (BTC) and 19.3 (ETH) annualized variance percentage points; panel regressions reveal that on-chain network congestion fees retain significant incremental explanatory power after controlling for VIX, DXY, and credit spreads—a novel identification of a blockchain-specific volatility channel. Fourth, rough volatility models (Hurst exponent H ≈ 0.08 for BTC) significantly outperform classical Heston specifications in fitting near-term implied volatility smiles, with RMSPE reductions of 31.7% for one-week expiry options. Fifth, CME Bitcoin Futures introduction produced a structural break in arbitrage efficiency, reducing basis mean-reversion halflives by 41.2% and lowering adverse-selection costs by 18.6 basis points. Sixth, on-chain DeFi perpetual protocols (GMX v2, dYdX v4) exhibit significantly higher adverse selection costs and lower price discovery shares (mean IS = 0.24) relative to centralized counterparts, but display timevarying convergence during U.S. regulatory uncertainty episodes. Our findings deliver unified implications for derivative pricing theory, risk management, and the architectural design of regulated cryptocurrency derivative markets.
Hamidreza Khankeh, Samaneh Motalebi, naajmeh yazdanparast, Abbas Naboureh
No abstract is available for this record.
Unnati Kadam
No abstract is available for this record.
Mohit Tiwari
No abstract is available for this record.
Nur Haliza Abdul Wahab, Juniardi Nur Fadila, Nur Faszha Razali, Keng Yinn Wong
High transaction costs remain a major barrier to the scalability of Ethereum-based decentralized applications (DApps), particularly when smart contracts are computationally inefficient. Although the Solidity compiler optimizer can reduce bytecode size and improve some low-level patterns, it does not fully address structural inefficiencies in storage layout and state mutation. This study introduces controlled empirical research on the topic of manual smart contract refactoring approaches with the aim of quantifying their impact on gas usage and execution cost in the Ethereum Virtual Machine (EVM). The Remix Integrated Development Environment (IDE) and a synchronized Go-Ethereum (Geth) node (version 1.13.5) were configured to create a controlled experimental environment. This environment was connected to the Sepolia Testnet to approximate conditions similar to the Ethereum Mainnet. The role of high-cost storage operations such as SSTORE was analyzed using opcode-level transaction traces, which were collected using debug_traceTransaction. The proposed refactoring plan implies the alignment of storage slots by systematically packing the variables and data location optimization (calldata and memory) to minimize unnecessary memory allocation. The experiments show gas reductions of up to 40.68% for storage-intensive functions, with an average reduction of 28.5% across all evaluated test cases. Moreover, the findings at the opcode level have shown that it is possible to reduce the costs of unnecessary storage writes without impacting the correct functional performance of the execution. Overall, the findings show that storage-aware manual refactoring is a viable strategy for improving runtime efficiency and reducing the execution cost of Layer-1 smart contracts.
Gauhar Ali, Sajid Hussain Shah, Muhammad Asim, Abdelhamied A. Ateya · 5 authors
The global energy sector is experiencing a significant revolution, propelled by the necessity to address climate change and shift towards sustainable energy sources. Particularly, the extensive implementation of distributed solar photovoltaic generation is converting traditional power grid systems into decentralized, prosumer-oriented energy grids. However, the traditional centralized energy trading frameworks cannot handle the complexity and volatility of a distributed grid, resulting in delay, costly transactions, a single point of failure, and insufficient transparency. Although blockchain (BC)-based peer-to-peer (P2P) energy trading presents an attractive solution, current models frequently neglect to ensure dependable and steady market convergence, instead concentrating mainly on transactional elements. This study proposed an innovative smart contract-based P2P renewable energy trading framework intended for decentralized grids. The proposed two-tiered framework, i.e., intra-microgrid and inter-microgrid layers, expands P2P trading from regional equilibrium to full grid connectivity. It utilizes a game-theoretic, iterative bidding approach, entirely automated by smart contracts. This method is formally proven to attain market convergence to a singular Nash equilibrium, optimizing utility for prosumers and consumers in the energy trading. Moreover, the decentralized ledger, smart contract-based market clearance, and limited disclosure of consumer/prosumer’s private data enhanced its resilience against replay, false data injection, and DoS/DDoS attacks. Additionally, the proposed energy trading market is proved monotonic and convergent formally by implementing a Promela model using the SPIN model checker.