This paper introduces Large Execution Models (LEMs), a novel deep learning framework that extends transformer-based architectures to address complex execution problems with flexible time boundaries and multiple execution constraints. Building upon recent advances in neural VWAP execution strategies, LEMs generalize the approach from fixed-duration orders to scenarios where execution duration is bounded between minimum and maximum time horizons, similar to share buyback contract structures. The proposed architecture decouples market information processing from execution allocation decisions: a common feature extraction pipeline using Temporal Kolmogorov-Arnold Networks (TKANs), Variable Selection Networks (VSNs), and multi-head attention mechanisms processes market data to create informational context, while independent allocation networks handle the specific execution logic for different scenarios (fixed quantity vs. fixed notional, buy vs. sell orders). This architectural separation enables a unified model to handle diverse execution objectives while leveraging shared market understanding across scenarios. Through comprehensive empirical evaluation on intraday cryptocurrency markets and multi-day equity trading using DOW Jones constituents, we demonstrate that LEMs achieve superior execution performance compared to traditional benchmarks by dynamically optimizing execution paths within flexible time constraints. The unified model architecture enables deployment across different execution scenarios (buy/sell orders, varying duration boundaries, volume/notional targets) through a single framework, providing significant operational advantages over asset-specific approaches.
Stefanos Chaliasos, Conner Swann, Sina Pilehchiha, Nicolas Mohnblatt · 6 authors
Rollups have become the de facto scalability solution for Ethereum, securing more than $55B in assets. They achieve scale by executing transactions on a Layer 2 ledger, while periodically posting data and finalizing state on the Layer 1, either optimistically or via validity proofs. Their fees must simultaneously reflect the pricing of three resources: L2 costs (e.g., execution), L1 DA, and underlying L1 gas costs for batch settlement and proof verification. In this work, we identify critical mis-pricings in existing rollup transaction fee mechanisms (TFMs) that allow for two powerful attacks. Firstly, an adversary can saturate the L2's DA batch capacity with compute-light data-heavy transactions, forcing low-gas transaction batches that enable both L2 DoS attacks, and finality-delay attacks. Secondly, by crafting prover killer transactions that maximize proving cycles relative to the gas charges, an adversary can effectively stall proof generation, delaying finality by hours and inflicting prover-side economic losses to the rollup at a minimal cost. We analyze the above attack vectors across the major Ethereum rollups, quantifying adversarial costs and protocol losses. We find that the first attack enables periodic DoS on rollups, lasting up to 30 minutes, at a cost below 2 ETH for most rollups. Moreover, we identify three rollups that are exposed to indefinite DoS at a cost of approximately 0.8 to 2.7 ETH per hour. The attack can be further modified to increase finalization delays by a factor of about 1.45x to 2.73x, compared to direct L1 blob-stuffing, depending on the rollup's parameters. Furthermore, we find that the prover killer attack induces a finalization latency increase of about 94x. Finally, we propose comprehensive mitigations to prevent these attacks and suggest how some practical uses of multi-dimensional rollup TFMs can rectify the identified mis-pricing attacks.
We formulate automated market maker (AMM) \emph{rebalancing} as a binary detection problem and study a hybrid quantum--classical self-attention block, \textbf{Quantum Adaptive Self-Attention (QASA)}. QASA constructs quantum queries/keys/values via variational quantum circuits (VQCs) and applies standard softmax attention over Pauli-$Z$ expectation vectors, yielding a drop-in attention module for financial time-series decision making. Using daily data for \textbf{BTCUSDC} over \textbf{Jan-2024--Jan-2025} with a 70/15/15 time-series split, we compare QASA against classical ensembles, a transformer, and pure quantum baselines under Return, Sharpe, and Max Drawdown. The \textbf{QASA-Sequence} variant attains the \emph{best single-model risk-adjusted performance} (\textbf{13.99\%} return; \textbf{Sharpe 1.76}), while hybrid models average \textbf{11.2\%} return (vs.\ 9.8\% classical; 4.4\% pure quantum), indicating a favorable performance--stability--cost trade-off.
Since its inception in 2009, cryptocurrencies have been a subject of debate in literature. In the general literature, the debate is mainly about the legality and application of these currencies while in Islamic literature, the debate is about its compliance with Sharia rules and directions. The primary objective of this study was to analyze current cryptocurrencies using a novel methodology and propose a new Islamic cryptocurrency, called âHalal Coinâ. To achieve the objectives of this study, a qualitative research method was followed by analyzing how the included cryptocurrencies work, analyzing some of its data for the period from January 1, 2023 to May 31,2025, and determining the characteristics of the proposed coin. Data used in this study were analyzed using descriptive statistics and the measure of âvalue at riskâ. The results revealed that none of the current cryptocurrencies are Sharia-compliant, and the proposed Halal coin is characterized by 15 attributes, including being accessible to all people, serving as a unit of account, and being free from high volatility.
In the current economic background, traditional supply chain finance mainly relies on the credit of core enterprises, but the credit is difficult to be effectively transmitted to small and medium-sized enterprises (SMEs) at the end of the supply chain. This paper examines the application of blockchain technology in SMEs supply chain finance through a case study of AntChain platform. The distributed ledger and smart contract technologies of blockchain can effectively solve the problems of information asymmetry, high financing costs and high financing risks in SMEs supply chain financing. After AntChain platform integrates the data of the upstream and downstream of the supply chain, it can provide more flexible financing for SMEs through the credit transfer of core enterprises. However, there are also certain deficiencies in actual operation. It is suggested to strengthen data privacy security, lower the entry barriers for SMEs and actively expand strategic partnerships to improve the development of AntChain platform.
This paper analyzes the influence of Bitcoin whales on price formation through the lens of market microstructure. Whales affect volatility and liquidity not only via large trades but also by sending strong informational signals. Despite a gradual diffusion of ownership and the rise of derivatives, whales remain structurally capable of destabilizing or stabilizing Bitcoin's market dynamics.
This article explores the transformative potential of Blockchain and distributed ledger technologies (DLT) in Afghanistanâs financial sector, amid a backdrop of systemic instability, infrastructural gaps, and geopolitical constraints. Drawing on an extensive review of digital banking development, expert interviews, and comparative global experiences, the study critically assesses Afghanistan's readiness to adopt Blockchain as a tool for financial inclusion, transparency, and institutional resilience. Although the formal banking system has largely regressed post-2021, grassroots crypto adoption reflects a latent readiness for decentralized solutions. The paper argues for a strategic, phased approach to Blockchain integration through regulatory reform, stakeholder engagement, and pilot implementations, particularly in land registration and remittance processing.
As Web3 matures, decentralized naming and storage systems, such as ENS, Unstoppable Domains, and IPFS, offer new paradigms for publishing and accessing web content without relying on centralized infrastructure.However, the process of retrieving content in such an environment remains fragmented, often dependent on vulnerable public gateways or centralized APIs.This paper investigates the resilience of content retrieval in decentralized systems, using Web3Compass as a case study.The system integrates real-time registry monitoring, onchain name resolution, and direct access to decentralized storage via self-hosted IPFS nodes.By avoiding reliance on third-party resolution services and fallback gateways except when necessary, Web3Compass provides a robust method for discovering and rendering Web3 websites.We detail the system's architecture, including resolver logic, node infrastructure, and content validation policies, and evaluate its robustness against gateway failure, incomplete pinning, and resolution inconsistencies.Our findings indicate that proactive pinning, resolver-specific logic, and local node infrastructure significantly improve access reliability, even under constrained network conditions.
The rapid growth of decentralized web technologies, such as IPFS, ENS, and Arweave, has enabled the creation and hosting of censorship-resistant, open-access websites.However, these systems suffer from a fundamental usability problem: decentralized websites are effectively invisible to the average user due to the absence of an indexing and discovery infrastructure.This paper introduces Web3 Compass, a search engine purpose-built for the decentralized internet.Unlike traditional search engines that rely on centralized servers and behavioral tracking, Web3 Compass discovers and indexes content from decentralized domains through real-time blockchain monitoring, resolver contract interactions, and a custom IPFS infrastructure.It outlines the visibility problem, examines failed or insufficient past solutions, and presents the architectural design of a hybrid, privacy-preserving search tool optimized for the decentralized web.The contribution aims to address the core bottleneck in Web3 usability by making decentralized content discoverable and accessible.
Large Language Models (LLMs) have enabled the emergence of autonomous agents capable of complex reasoning, planning, and interaction. However, coordinating such agents at scale remains a fundamental challenge, particularly in decentralized environments where communication lacks transparency and agent behavior cannot be shaped through centralized incentives. We propose a blockchain-based framework that enables transparent agent registration, verifiable task allocation, and dynamic reputation tracking through smart contracts. The core of our design lies in two mechanisms: a matching score-based task allocation protocol that evaluates agents by reputation, capability match, and workload; and a behavior-shaping incentive mechanism that adjusts agent behavior via feedback on performance and reward. Our implementation integrates GPT-4 agents with Solidity contracts and demonstrates, through 50-round simulations, strong task success rates, stable utility distribution, and emergent agent specialization. The results underscore the potential for trustworthy, incentive-compatible multi-agent coordination in open environments.
The global carbon credit trading market faces significant challenges including lack of real-time verification, double-spending issues, and insufficient transparency in emission measurements. This paper presents a novel blockchain-enabled framework integrating Internet of Things (IoT) sensors for automated carbon credit generation and trading. Our proposed system combines tamper-proof IoT sensor networks with smart contract automation to address current limitations in carbon credit systems. The methodology employs distributed sensor nodes equipped with CO2, temperature, and humidity sensors connected to an Ethereum-based blockchain network. Through extensive simulation and real-world testing, our system demonstrates 99.2% accuracy in emission measurement and real-time carbon credit generation. The framework reduces verification time by 87% compared to traditional manual verification processes while ensuring immutable transaction records. Key contributions include: (1) a decentralized IoT-blockchain architecture for carbon monitoring, (2) smart contract protocols for automated credit generation, (3) a novel consensus mechanism for sensor data validation, and (4) comprehensive security analysis demonstrating resistance to common blockchain attacks. Results indicate significant potential for transforming carbon credit markets through enhanced transparency, reduced fraud, and improved environmental monitoring accuracy.
Zero-knowledge rollups rely on provers to generate multi-step state transition proofs under strict finality and availability constraints. These steps require expensive hardware (e.g., GPUs), and finality is reached only once all stages complete and results are posted on-chain. As rollups scale, staying economically viable becomes increasingly difficult due to rising throughput, fast finality demands, volatile gas prices, and dynamic resource needs. We base our study on Halo2-based proving systems and identify transactions per second (TPS), average gas usage, and finality time as key cost drivers. To address this, we propose a parametric cost model that captures rollup-specific constraints and ensures provers can keep up with incoming transaction load. We formulate this model as a constraint system and solve it using the Z3 SMT solver to find cost-optimal configurations. To validate our approach, we implement a simulator that detects lag and estimates operational costs. Our method shows a potential cost reduction of up to 70\%.
This paper presents the design and implementation of a blockchain-secured system for monitoring driver sobriety and real-time geolocation. The proposed platform integrates a Modular Sensor Battery (MSB) for detecting alcohol concentration in exhaled air, a centralized Data Collection Platform (DC Platform) for real-time data visualization and storage, and a complementary physiological monitoring deviceâthe IoT Fit-Bit Smart Band (IFSB)âwhich captures heart rate and blood oxygen saturation as alternative indicators when breath-based sensing may be compromised. The MSB, the DC Platform, integration with the IoT FitBit Smart Band, and the blockchain-based data management architecture represent the authorsâ direct contribution to both the conceptual design and technical implementation. These elements are introduced as part of a unified, fully integrated system designed to enable non-invasive sobriety monitoring and secure data integrity in vehicular contexts. To ensure data authenticity, a custom Ethereum smart contract stores cryptographic hashes of sensor readings, enabling decentralized, tamper-evident verification without exposing sensitive medical information. The system was validated in a controlled experimental environment, confirming its operational robustness and demonstrating its potential to improve road safety through secure, real-time sobriety detection and geolocation tracking.
In the last decade, cryptocurrency has emerged as a major financial and technological phenomenon. This research explores the use of Bitcoin in Yemen. Yemen is a country currently facing a severe humanitarian and economic crisis. The study aims to analyze the opportunities offered by Bitcoin. These opportunities could help overcome traditional financial constraints. The research also examines the challenges that hinder its spread and use. An analytical descriptive methodology was used. The study looked at economic, legal, and social aspects. The results showed that Bitcoin provides real opportunities. It can facilitate financial transfers and offer alternatives to broken banking systems. However, it also faces significant challenges. These include the absence of a legal framework. Other challenges are weak infrastructure and the risks of security breaches and fraud. The research also addressed the legal stance towards these currencies, which remains unclear. The study concludes with recommendations. It provides suggestions for relevant authorities and users. The goal is to maximize benefits and reduce the risks of cryptocurrencies. It emphasizes the need for effective regulations. This will ensure safe and sustainable use.
The development of digital technology has driven the transformation of the global economy, including in Indonesia, through the commercialization of digital assets such as creative works, Non-Fungible Tokens (NFTs), and e-commerce platforms. However, the national legal system is still unable to accommodate these dynamics comprehensively. This study aims to analyze the effectiveness of legal protection of CopyrightCopyright as a digital asset in technology-based transactions, using normative legal methods and legislative, conceptual, and comparative legal approaches. The results of the study show that Law Number 28 of 2014 concerning Copyright and related regulations still has a gap in norms in dealing with new forms of digital intellectual property, weak law enforcement, and limited technical understanding by law enforcement officers. In addition, the less-than-optimal regulation in the financial, taxation, and personal data protection sectors increases the legal risks for digital economy actors, especially MSMEs and content creators. Therefore, responsive legal reforms are needed to strengthen the digital justice system, integrate technologies such as blockchain and AI, and increase legal literacy and coordination between institutions. This reform is important to create a fair, safe, and sustainable digital ecosystem that supports the growth of the national creative economy.
In the world of increasing population with ever increasing strain on law enforcement agencies and judiciary, lack of imparting justice in time has become a major concern. The lack of timely justice has adversely affected the societyâs ability to both administer and regulate public relations and affairs. In the middle of such concerns, Blockchain and Smart Contracts can play a pivotal role in managing society and ensuring a balance between criminal intent and legal sanction. Blockchain is a decentralized distributed framework where all nodes in the network collaborate on an equal footing to maintain necessary properties and functions. First introduced in 2008 via a seminal work âBitcoin,â the principles underlying cryptocurrency have shown immense potential. As of 2023, Blockchain is an institutional technology reshaping the current internet (web version 2.0) forcing it to evolve to web 3.0. It is the basis of âsmart contracts,â âdistributed applications,â âtoken economies and âdecentralized autonomous organization.â This paper dwells on two such applications, namely, cryptocurrency and smart contracts wherein we explain the technologies while highlighting legal challenges and open questions which need significant attention.
Users of blockchains value scalability, expecting fast confirmations and immediate transaction processing. Odontoceti, the latest in DAG-based consensus, addresses these concerns by prioritizing low latency and high throughput, making a strategic trade-off in security by operating with a 20% fault tolerance instead of the established 33% level. It is the first DAG-based protocol to achieve commitment in just two communication rounds, delivering median latency of 300 milliseconds while processing 10,000 transactions per second under realistic network conditions. Odontoceti operates with n = 5f + 1 validators and creates an uncertified DAG with a novel decision rule for committing blocks. The protocol includes an optimization that advances progress when participants are slow, benefiting crash fault scenarios which are more common in practice than Byzantine faults. Evaluation results demonstrate 20-25% latency improvements compared to an existing production protocol, validating that reducing wave length from three rounds to two rounds yields meaningful performance benefits. This paper establishes the practical viability of lower fault tolerance consensus protocols for blockchains.
Blockchain consensus, rooted in the principle ``don't trust, verify'', limits access to real-world data, which may be ambiguous or inaccessible to some participants. Oracles address this limitation by supplying data to blockchains, but existing solutions may reduce autonomy, transparency, or reintroduce the need for trust. We propose Swarm Oracle: a decentralized network of autonomous robots -- that is, a robot swarm -- that use onboard sensors and peer-to-peer communication to collectively verify real-world data and provide it to smart contracts on public blockchains. Swarm Oracle leverages the built-in decentralization, fault tolerance and mobility of robot swarms, which can flexibly adapt to meet information requests on-demand, even in remote locations. Unlike typical cooperative robot swarms, Swarm Oracle integrates robots from multiple stakeholders, protecting the system from single-party biases but also introducing potential adversarial behavior. To ensure the secure, trustless and global consensus required by blockchains, we employ a Byzantine fault-tolerant protocol that enables robots from different stakeholders to operate together, reaching social agreements of higher quality than the estimates of individual robots. Through extensive experiments using both real and simulated robots, we showcase how consensus on uncertain environmental information can be achieved, despite several types of attacks orchestrated by large proportions of the robots, and how a reputation system based on blockchain tokens lets Swarm Oracle autonomously recover from faults and attacks, a requirement for long-term operation.
Qianyu Yu, Giuliano Losa, Nibesh Shrestha, Xuechao Wang
To maximize performance, many modern blockchain systems rely on eventually-synchronous, Byzantine fault-tolerant (BFT) consensus protocols. Two protocol designs have emerged in this space: protocols that minimize latency using a leader that drives both data dissemination and consensus, and protocols that maximize throughput using a separate, asynchronous data dissemination layer. Recent protocols such as Partially-Synchronous Bullshark and Sailfish combine elements of both approaches by using a DAG to enable parallel data dissemination and a leader that paces DAG formation. This improves latency while achieving state-of-the-art throughput. Yet the latency of leader-based protocols is still better under moderate loads, which are common in practice. We present Angelfish, a hybrid protocol that adapts smoothly across this design space, from leader-based to Sailfish-like DAG-based consensus. Angelfish lets a dynamically adjusted subset of parties use best-effort broadcast to issue lightweight votes instead of reliably broadcasting costlier DAG vertices. This reduces communication, helps lagging nodes catch up, and lowers latency in practice compared to prior DAG-based protocols. Our empirical evaluation shows that Angelfish attains state-of-the-art peak throughput while significantly lowering latency under moderate throughput, delivering the best of both worlds.
Bitcoin's consensus rules are encoded in the implementation of its reference client: "The code is the spec." Yet this code is unsuitable for formal verification due to side effects, mutable state, concurrency, and legacy design. A standalone formal specification would enable verification both across versions of the reference client and against new client implementations, strengthening decentralization by reducing the risk of consensus-splitting bugs. Yet such a specification has long been considered intractable given the complexity of Bitcoin's consensus logic. We demonstrate a compact, executable, declarative C++ specification of Bitcoin consensus rules that syncs mainnet to tip in a few hours on a single thread. We also introduce the Hornet Domain-Specific Language (DSL) specifically designed to encode these rules unambiguously for execution, enabling formal reasoning, consensus code generation, and AI-driven adversarial testing. Our spec-driven client Hornet Node offers a modern and modular complement to the reference client. Its clear, idiomatic style makes it suitable for education, while its performance makes it ideal for experimentation. We highlight architectural contributions such as its layered design, efficient data structures, and strong separation of concerns, supported by production-quality code examples. We argue that Hornet Node and Hornet DSL together provide the first credible path toward a pure, formal, executable specification of Bitcoin consensus.
Digital payments have grown exponentially but face risks such as fraud, account takeover, and unauthorized transactions. This paper explores how blockchain technology, with its decentralized ledger, cryptographic integrity, and smart contracts, can secure digital payments and prevent fraud. We propose a permissioned blockchain architecture for payment systems, integrating identity management, escrow-based smart contracts, and audit-ready transaction logs. Illustrative simulations compare fraud-risk indices, transaction confirmation time, and per-transaction cost across traditional payment gateways and blockchain systems. The results indicate that blockchain can reduce fraud exposure while maintaining near real-time settlement. Challenges such as scalability, privacy, and regulatory compliance are also discussed. This study highlights blockchain?s potential as a preventive, secure mechanism for digital payments and sets the stage for future research integrating zero-knowledge proofs and federated learning.
The problem of surprise medical billing has become quite ubiquitous in the American healthcare system, impacting the wallets of insured citizens adversely as they unknowingly seek the services of providers who are out of network. Although the No Surprises Act has created federal safeguards to prevent surprise bills, there are portions in the regulatory system that have not been addressed sufficiently, and a system-wide approach is needed for technical solutions. The approach is transformative as the Integrated Financial Systems (IFS) are increasingly offered on the basis of advanced interoperability standards like Fast Healthcare Interoperability Resources (FHIR) and promising emerging technologies such as blockchain and distributed ledger systems. These technologies bring more transparent, efficient, and secure healthcare billing ecosystems, which are beneficial to all stakeholders because patients achieve greater financial clarity and simplified billing procedures, providers realize a streamlined approach to revenue cycle management and fewer administrative tasks, and insurers achieve faster claims processing and fraud detection. The rise of IFS brings with it critical, ethically-driven concerns surrounding algorithmic decision-making and data privacy that would require the implementation of explainable AI, routine bias evaluation, and human judgment via Human-in-the-Loop frameworks to warrant fair results among various patient groups.
The article is devoted to the theoretical and methodological justification of the impact of decentralization reform on the financial capacity of rural communities using the example of Zakarpattia Oblast in the context of martial law and profound socio-economic transformations. The content of decentralization as a key element of multi-level public administration is revealed, and its role in redistributing powers, resources, and responsibilities between the central government and local self-government, as well as in the formation of capable territorial communities, is clarified. Based on the Constitution of Ukraine, the fundamental laws on local self-government, and strategic documents of state regional policy, the institutional foundations of financial decentralization and the formation of local budgetsâ revenue base are analyzed. A methodological approach to assessing the financial capacity of communities is proposed, based on the use of an integral index and a system of eleven indicators (revenues, expenditures, budget structure, share of transfers, capital investments, etc.), considering data from the ULEAD with Europe program and the specifics of the war period. Based on empirical data from 2023â2024, differences in financial capacity across rural, settlement, and urban communities were revealed. Trends in the share of communities with high, optimal, satisfactory, low, and critical levels of capacity were outlined, including a decrease in the share of critically weak communities and a gradual strengthening of individual rural communities. Specific attention is paid to the analysis of the financial situation in the communities of Zakarpattia Oblast, where both deterioration in indicators for individual territories and positive examples of capacity growth through intermunicipal cooperation, participation in international projects, and the intensification of local economic development have been recorded. The expediency of using an integrated financial capacity index as a tool for monitoring and justifying targeted state and regional policy measures to support rural communities is demonstrated. Keywords: decentralization, capacity, socio-economic development, finance, rural areas, territorial communities, competitiveness.
Benjamin Mudiangombe Mudiangombe, John Weirstrass Muteba Mwamba
This study explores the new insights into the integration and dynamic asymmetric volatility risk spillovers between Bitcoin, currency pairs (USD/ZAR, GBP/ZAR and EUR/ZAR), and traditional financial assets (ALSI, Bond, and Gold) in South Africa using daily data spanning the period from 2010 to 2024 and employing Time-Varying Parameter Vector Autoregression (TVP-VAR) and wavelet coherence. The findings revealed strengthened integration between traditional financial assets and currency pairs, as well as weak integration with BTC/ZAR. Furthermore, BTC/ZAR and traditional financial assets were receivers of shocks, while the currency pairs were transmitters of spillovers. Gold emerged as an attractive investment during periods of inflation or currency devaluation. However, the assets have a total connectedness index of 28.37%, offering a reduced systemic risk. Distinct patterns were observed in the short, medium, and long term in time scales and frequency. There is a diversification benefit and potential hedging strategies due to goldâs negative influence on BTC/ZAR. Bitcoinâs high volatility and lack of regulatory oversight continue to be deterrents for institutional investors. This study lays a solid foundation for understanding the financial dynamics in South Africa, offering valuable insights for investors and policymakers interested in the intricate linkages between BTC/ZAR, currency pairs, and traditional financial assets, allowing for more targeted policy measures.