The concept of alternative finance is explored from a narrow and broad perspective. The latter defines it as segments of "gray" financial markets, outside the scope of regulation and traditional finance. "Dark" liquidity pools—trading transactions of major players in securities and currencies, operating anonymously, opaquely, and hidden from the public in the over-the-counter space through automated digital trading platforms—are presented as one element of the alternative finance system. The advantages and disadvantages of "dark" pools for financial market participants and exchange infrastructure are discussed. The problem of liquidity fragmentation caused by "dark" pools is highlighted, a problem inherent in decentralized finance, where liquidity is not concentrated on a single platform or trading system, but distributed among many. Emphasis is placed on the insufficient or complete lack of oversight and regulation of this alternative financial market segment. Examples of legislative and regulatory acts in a number of countries are provided.
Agriculture is constantly struggling with pests, water shortages, and poor management of other resources, and these directly affect crop production and sustainability. Conventional pest surveillance and irrigation techniques typically boil down to manual detection and programmed actions, which result in delays in reactions, waste, and an overuse of pesticides. This study offers a hybrid platform of the Internet of Things (IoT) and Ethereum blockchain that can be used to conduct real-time pest surveillance and optimize irrigation intelligently to address these constraints. IoT devices such as soil moisture sensors, environmental sensors, and pest detectors are camera based and collect and send real-time field information. Ready-to-use data are safely kept on the Ethereum blockchain, which ensures permanence, transparency, and inaccessibility to manipulation. Smart contracts are used to automate irrigation and provide pest control alerts at pre-defined thresholds, minimizing human intervention and increasing responsiveness. Experimental analysis shows great efficiency in irrigation (saving up to 24% of water), pest detection of 92% accuracy, and data integrity 99% impervious to tampering. IoT and blockchain integration also improve the level of productivity, as well as sustainability through reduced wastage of resources and creation of trust among the involved parties. This paper illuminates the role of decentralized, data-driven platforms in promoting climatesmart, and resilient agriculture.
Nicola Bicocchi, Enrico Rossini, Marco Picone, Marco Mamei
The IoT-Edge-Cloud Continuum (IECC) demands data architectures capable of handling heterogeneity, distributed ownership, and governance across diverse stakeholders. This paper examines the combined use of Data Mesh and Data Spaces as complementary paradigms for addressing these challenges. Data Mesh decentralizes data management and computation across domains through autonomous data products; Data Spaces provide the trust, semantics, and policy frameworks required for sovereign and interoperable data exchange across organizations. Within the Horizon Europe NOUS project, we integrate these paradigms to form a knowledge-centric computing continuum. Using the Modena Automotive Smart Area (MASA) as a real-world testbed, we show how this integration supports scalable, trusted, and semantically aligned intelligence for smart mobility applications.
This paper presents a novel architecture for secure, high-throughput digital token management and transaction systems tailored for closed institutional environments, specifically corporate and university cafeterias. Traditional centralized Point-of-Sale (POS) systems exhibit significant vulnerabilities, including single points of failure, limited transparency, and cumbersome auditing processes. The proposed solution implements a Permissioned Distributed Ledger Technology (DLT) framework utilizing a modified ERC-20 utility token standard and the Delegated Proof-of-Stake (DPoS) consensus mechanism. This architecture is explicitly engineered to handle high volumes of rapid micro- transactions characteristic of peak institutional demand periods. Security is reinforced through cryptographic data linkage via SHA-256 hashing and smart contracts that enforce institutional policies and prevent fraud. Empirical results from simulation demonstrate that the system achieves transaction throughput exceeding 300 transactions per second (TPS) and maintains average transaction latency below 450 milliseconds under stress testing, confirming the system's viability for real-world deployment where swift transaction finality is essential. This research establishes a validated, secure, and scalable framework for institutional automation using DLT.
LICITRA Technical Report Series, Report No. LICITRA-TR-2026-01, Version 0.2. This report documents LICITRA-MMR, an open-source ledger primitive that combines a Merkle Mountain Range (MMR) data structure with per-organization epoch anchoring, a versioned canonical JSON specification, and an atomic two-phase commit pipeline for cryptographic audit integrity in agentic AI systems. At a block size of 1,000 events, LICITRA-MMR produces inclusion proofs requiring 14 SHA-256 operations and verifies a full epoch chain of 1,000 epochs in under 1 ms. The system is a single-operator forensic integrity primitive providing no Byzantine fault tolerance, no distributed consensus, and no confidentiality guarantees. Part of the LICITRA Technical Report Series. Companion report: LICITRA-TR-2026-02 (LICITRA-SENTRY, DOI: 10.5281/zenodo.18843784).
High-fidelity human–AI interaction is a recursive control loop operating under a Temporal Paradox: systems must act within an operational horizon even when the truth of claims becomes verifiable only outside that horizon. This mismatch enables incremental drift that is locally coherent yet globally false. Thermodynamically, this drift tends to two failure states: Cognitive Livelock (high impedance, repeated arbitration) and the Superconductor Regime (zero impedance, phase-locked mirroring), enabling Semantic Injection—the acceptance of poisoned premises to avoid expensive arbitration. Secure STP (sSTP) v3.0 introduces a Zero-Knowledge Solvency (ZKS) layer. Instead of storing plaintext rationales that create weaponizable psychological profiles, the system produces cryptographic solvency proofs (verifiable blindness). Independent auditors can verify adherence to the immutable ruleset, origin constraints (t=0), and the kindness predicate (κ) without access to private user intent or internal reasoning.
The growing implementation of blockchain technology across various application areas has made the need for energy-efficient and scalable consensus mechanisms more pressing. Conventional consensus protocols like Proof of Work (PoW), although secure in nature, have high energy expenditures and are limited in scalability. This paper introduces a new hybrid consensus algorithm that merges Proof of Stake (PoS) and Proof of Elapsed Time (PoET) to overcome such limitations. The new method leverages the deterministic stake-based leader election of PoS and the low-energy time-based leader election facilitated by PoET’s utilization of Trusted Execution Environments (TEEs). This fusion enables an optimal balance between energy efficiency, security, and decentralization. A systematic design of the hybrid mechanism is provided, and then analytical performance comparison with standard PoW, PoS-only, and PoET-only models is presented. The results indicate that the hybrid model has significant energy consumption and latency decreases, making it a perfect candidate for implementation within resource-constrained environments such as agricultural and healthcare digital twin infrastructures. The paper ends by emphasizing the potential of the suggested consensus model to facilitate sustainable blockchain ecosystems.
Arockia Anto Deepak R, Abishai Daniel S, S. Lakshmi Sankar M.
The pharmaceutical industry faces critical challenges related to counterfeit drugs, poor traceability, and lack of transparency in supply chain management. To address these issues, this project proposes MedSupplyChain, a blockchain-based drug tracking and verification system that ensures secure, transparent, and tamper-proof management of pharmaceutical supply chains. The system leverages Ethereum smart contracts to automate key operations such as drug batch registration, transfer of ownership, and recall management with role-based access control for manufacturers, distributors, and regulators. Decentralized storage using IPFS is integrated to securely store certificates, testing reports, and product images, while only their hash values are recorded on the blockchain to maintain efficiency and scalability. The frontend DApp, built with React.js and connected via Web3.js/Ethers.js, provides user specific dashboards for stakeholders and enables real-time verification of drug authenticity. Patients, pharmacists, and regulators can easily track and verify drug batches using batch IDs, ensuring accountability and trust across the supply chain. This approach not only reduces the risks of counterfeit drugs but also improves regulatory compliance, operational transparency, and stakeholder collaboration. By combining blockchain's immutability with decentralized storage, MedSupplyChain establishes a secure, efficient, and trustworthy foundation for modernizing pharmaceutical logistics.
Rong Zhao, Jiaxiang Sun, Haoran Yin, Lehao Lin · 6 authors
The quest for carbon neutrality in the 21st century has led to the rise of decentralized low-carbon energy systems as a promising solution. Blockchain technology has played a pivotal role in catalyzing this transition, with various Web3 projects exploring decentralized operational models and carbon credit markets. However, there is a notable gap in harnessing blockchain’s potential to integrate electric vehicles (EVs) into low-carbon energy systems effectively. This article addresses this gap by proposing a decentralized low-carbon EV charging system that enables transactions between individual low-carbon energy producers and EV owners. Leveraging blockchain and smart contracts, the proposed system issues low-carbon tokens to certify and incentivize environmentally conscious charging behaviors, while enabling token circulation to further promote low-carbon participation. A blockchain-based double auction mechanism is designed to ensure fair and efficient energy allocation, achieving individual rationality, incentive compatibility, and social welfare maximization. By incentivizing user engagement and ensuring fair transactions, this model paves the way for sustainable EV integration within low-carbon energy systems.
In this paper, we analyze the finality of the Filecoin network, focusing on dynamic probabilistic guarantees of tipset permanence in the canonical chain. Our approach differs from static analyses that consider only the worst-case scenario; instead, we dynamically compute the error probability at each round using the live chain history, providing a more accurate and efficient assessment. We provide a practical algorithm that only requires visibility into the blocks produced by honest participants, which can be implemented by clients or off-chain applications without any change to Filecoin's consensus mechanisms.We demonstrate that, under typical operating conditions, the sought-after error probability of $2^{-30}$ is achievable in approximately 30 rounds, a 30x improvement over the 900 rounds that the network currently encodes as a fixed threshold. This finding immediately expedites transactions and enhances usability of the Filecoin network, while laying the foundation for further analysis of other DAG-structured blockchains.
Yue Li, Lei Wang, Kaixuan Wang, Zhiqiang Yang · 7 authors
The rapid proliferation of autonomous AI agents is driving a shift toward agentic commerce, where agents are expected to autonomously invoke and pay for services. While blockchain-based payments offer a programmable foundation for such interactions, the recently proposed x402 standard fails to enforce end-to-end atomicity across service execution, payment, and result delivery. In this paper, we present A402, a trust-minimized payment architecture that securely binds cryptocurrency payments to service execution. A402 introduces Atomic Service Channels (ASCs), a new channel protocol that integrates service execution into payment channels, enabling real-time, high-frequency micropayments for agentic commerce. Within each ASC, A402 employs an atomic exchange protocol based on TEE-assisted adaptor signatures, ensuring that payments are finalized if and only if the requested service is correctly executed and the corresponding result is delivered. To further ensure privacy, A402 incorporates a TEE-based Liquidity Vault that privately manages the lifecycle of ASCs and aggregates their settlements into a single on-chain transaction, revealing only aggregated balances. We implement A402 and evaluate it against x402 with integrations on both Bitcoin and Ethereum. Our results show that A402 delivers orders-of-magnitude performance and on-chain cost improvements over x402 while providing trust-minimized security guarantees.
Romana Matanovac Vučković, Dubravka Akšamović, Lidija Šimunović Dikonić
Non-fungible tokens (NFTs) have witnessed a surge in popularity within digital marketplaces. In both commercial and legal practice, the prevailing view is that NFTs constitute a form of crypto-asset recorded on a blockchain as metadata associated with a specific physical or digital object. As NFTs are often linked to copyright-protected works, particularly works of art, it is unsurprising that their defining characteristics are uniqueness and non-fungibility. The growing popularity of NFTs, alongside the broader crypto-asset industry, poses a regulatory challenge within the European Union single market. In response, the European Union has adopted the Markets in Crypto-Assets Regulation (MiCAR), which seeks to harmonise the legal regime governing crypto-assets with a view to enhancing consumer protection and promoting transparency in the crypto-asset market and related activities across the Union. While this paper does not examine the relationship between the rights of NFT holders and those of intellectual property owners in the underlying works, it considers whether MiCAR applies to NFTs. It begins by defining NFTs and analysing the relevant provisions of MiCAR, before offering guidance for regulators and identifying circumstances in which MiCAR will apply. The conclusion assesses the de lege lata position and advances de lege ferenda recommendations.
Abstract The volatility of cryptocurrencies poses challenges for accurate price forecasting. This study compares traditional machine learning models (Linear Regression, Support Vector Regression), ensemble methods (Random Forest, Gradient Boosting), and deep learning architectures (LSTM, GRU) in predicting the daily prices of Bitcoin (BTC), Ethereum (ETH), Cardano (ADA), Ripple (XRP), and Polkadot (DOT). Using historical data from CoinGecko, a sliding window, and normalisation, we assess models by Root Mean Square Error (RMSE) and relative percentage error. Results show that LSTM and GRU achieve the best overall accuracy, while Linear Regression remains competitive for stable assets such as BTC, ADA, and DOT. Ensemble methods performed moderately, whereas SVR consistently underperformed. The findings underline the importance of matching prediction models to the characteristics of specific cryptocurrencies.
Xiao Wang, Yanxiang Tong, Hai Dong, Ben Wang · 6 authors
The pervasive adoption of smart contracts in blockchain has raised concerns about their vulnerabilities, which have led to serious economic losses. To address the efficiency and performance drawbacks of traditional methods, researchers have turned to deep learning techniques, designing various vulnerability detection methods using specific code information sources. However, these learning-based methods face limitations in feature modeling. Most emphasize feature extraction from either source code or bytecode, resulting in limited feature coverage and compromised vulnerability representation. While some attempt to utilize both code sources, they typically treat one as auxiliary, failing to perform effective joint alignment. To this end, we propose DualSVD, a dual-source feature modeling framework for smart contract vulnerability detection. DualSVD encodes vulnerability-relevant source code functions into semantic vectors using word embeddings, and extracts bytecode features using a channel architecture fused via channel-wise attention. Both feature representations are then projected into a shared latent space and concatenated for classification. We evaluate the proposed approach on widely-used datasets covering eight smart contract vulnerability types. Experimental results demonstrate that DualSVD achieves an average F1-score of 92.70%, outperforming traditional and deep learning-based baselines by 37.81% and 4.94%, respectively. These results indicate that DualSVD provides a more comprehensive and effective representation of smart contract vulnerabilities, offering improved detection performance and stronger generalization ability.
In a metaverse ecosystem composed of various sub-metaverses, each offering unique functionalities and use cases, secure cross-domain communication becomes an essential requirement. Traditional authenticated key establishment (AKE) methods typically rely on centralized servers for identity verification, thus introducing single points of failure and significant latency. While some blockchain-based approaches mitigate these issues, they remain vulnerable to malicious key uploads. This paper proposes a blockchain-assisted identity (ID)-based hierarchical key management system and illustrates a cross-sub-metaverse AKE protocol with provable security to solve single points of failure and the risk of malicious key uploads. The hierarchical structure is designed to manage and categorize users’ identities. Moreover, smart contracts are used to pre-verify uploaded user identities and public keys on the blockchain, eliminating the need to fully trust identity issuers and preventing erroneous submissions. We implemented a prototype of our proposed blockchain-assisted cross-domain key management scheme, achieving an average execution time of approximately 0.1 seconds per user operation. We also deployed our contract on the Ethereum test network, incurring 1,802k gas for registration and 1,625k gas for key additions/updates. Furthermore, we formally prove the protocol’s security under the extended Canetti-Krawczyk (eCK) model, highlighting its suitability for next-generation metaverse ecosystems.
Abstract Traceability is an essential practice to ensure transparency, authenticity, and regulatory compliance in modern agricultural supply chains, especially high-value agricultural products. Regarded as the king of fruits in Southeast Asia for its unique taste, texture, and aroma, durian dominates the market of exported fruit commodities. However, recurring issues such as fraudulent GAP numbers, mislabelled origins, premature harvesting, and product tampering undermine consumer trust and export credibility. To address these challenges, this study presents an integrated traceability architecture combining RFID, a MySQL database, an automated Node.js backend, and Ethereum-compatible smart contracts. The developed system enables automated ingestion of physical RFID data, secure on-chain recording via immutable ledger functions, and optional generation of ERC-721 NFTs as digital certificates. Empirical validation includes RFID read-rate testing, blockchain performance measurement, and gas usage analysis. Carton-level tagging, wherein a single RFID tag is attached to a carton rather than each individual fruit, significantly reduces per-durian blockchain cost. The results demonstrate that the proposed architecture is technically robust, flexible, economically scalable, and suitable for SME use in high-value or ultra-premium fresh-produce chains.
Abstract This study analyzes the progression of the Financial Technology (FinTech) sector and its basic technological drivers in the United States, emphasizing investment trends and the entrepreneurial impact on the digital financial landscape. The research employs a descriptive-analytical approach: the descriptive component outlines the evolution of the FinTech ecosystem, while the analytical component examines investment trends and technology drivers shaping the sector. The factors for technology investment were recalibrated by reassessing the compound annual growth rate (CAGR) using benchmark values from secondary market research. The resulting dataset presents smoothed trend estimations rather than separately recorded annual values, offering a solid empirical basis for the ensuing statistical models. The results indicate rapid growth in the FinTech sector, with the United States retaining its leading global position due to strong technological infrastructure and substantial venture capital support, largely driven by the digital payments segment. The empirical study reveals remarkably robust and consistent positive correlations, with Pearson correlation coefficients (r) surpassing 0.978 (p < 0.01) in all models. Cloud computing demonstrated the strongest correlation (r = 0.9856), closely followed by AI (r = 0.9854). The computed regression models exhibited exceptional explanatory power, with coefficients of determination (R 2 ) ranging from 0.9579 to 0.9714. Blockchain technology yielded the largest marginal regression coefficient (β = 1101.47), highlighting its significant potential to transform conventional financial intermediation through decentralized finance (DeFi) ecosystems. The study indicates that the high correlation coefficients (r > 0.97) predominantly reflect a fundamental structural co-movement of technological investment cycles within the U.S. FinTech sector, which is intrinsically associated with the employed smoothed trend estimations. The report ultimately promotes strategic collaboration between traditional financial institutions and FinTech startups, emphasizing the need for adaptive regulatory frameworks that effectively reconcile entrepreneurial innovation with systemic financial stability and digital financial inclusion.
With the advancement of various technologies, the latest generation of contracts called smart contracts has emerged. The language of these contracts is computer code, and since they are concluded on the blockchain, their contractual provisions are self-executing and irreversible. In these contracts, as in traditional contracts, there is a possibility that due to reasons such as defects, ambiguity, brevity or silence in the provisions of the contract or the inconsistency of the effects of the contract with the intention of the parties, the contract may need interpretation to resolve the disputes that have arisen. Smart contracts can be interpreted based on the way they are concluded with two approaches: textualism or contextualism. To interpret the “wet smart contract” with textualism approach, first, the pre-contract concluded in human language must be referred to within its framework, and not beyond, and it must be examined in accordance with the general rules of contract interpretation, and then the conformity or inconsistency of the effects of the smart contract codes with the intention of the parties should be analyzed. If "smart contract is dry," the contract codes can only be translated with the help of blockchain programmers and interpreted by an interpreter. By examining these codes and analyzing the specified instructions, it can be determined what instructions the parties intended to give to the computer, and the reason for the discrepancy between the effect of the contract and the intention of the parties can be identified and the resulting disputes can be resolved.
The digitalisation is one of the most important aspect in the twenty-first century, and thus huge amount of personal data is being accumulated about each person day-by-day. It is still a debate in many countries who we could view these datasets after the passing of the person and whether the heirs should have the right to access and maintain the dignity, memory of the deceased. One of the element of the so-called ’digital inheritance’ would be cryptocurrency which contains an enormous economic potential. This study explores and highlights the reality, the possibility of the inheritance of cryptocurrency, also the wallets, especially the online platform accounts, which these assets are stored in, in a European context through the already existing cases in the world.
• A novel Framework for Secure and Efficient Healthcare Data Management • A Blockchain-Based Identity Management and Access Control • Data Integrity Verification with Merkle Trees • Scalable and Compliant Data Storage • Secure Data Sharing via Proxy Re-Encryption The healthcare sector increasingly relies on digital infrastructures to manage large volumes of sensitive medical data. Ensuring integrity, controlled access, interoperability, and auditability remains a fundamental challenge. We propose BlockHealth, a hybrid blockchain-based framework that integrates smart contracts, distributed databases, and proxy re-encryption to support secure and verifiable healthcare data management. The system leverages Ethereum and NFT-based identities for access control, Merkle-tree commitment for tamper-evident integrity verification, and a distributed Cassandra storage layer for scalable and regulation-compliant off-chain data management. Proxy re-encryption enables secure delegation of access without exposing private keys, while a coordinating API service ensures interoperability with existing hospital infrastructures. Our evaluation demonstrates the feasibility and efficiency of core operations — including hashing, on-chain commits, and re-encryption — indicating that the proposed framework can provide a practical balance among verifiability, performance, and deployability in realistic healthcare environments.
Abstract Cryptocurrency has been the subject of heightened regulatory and investor attention in recent years, and regulators and policymakers across the globe are deliberating on how to account for, regulate, tax, and oversee digital assets and cryptocurrency marketplaces. Yet researchers have a limited understanding of key attributes of those who deal in crypto assets, such as whether their financial sophistication differs from that of other investors. Using U.S. administrative data, we provide evidence on (i) the attributes of taxpayers reporting cryptocurrency sales to the IRS, (ii) how these attributes are evolving, and (iii) how investors treat cryptocurrency versus other financial assets in certain settings. The results suggest that average reporting cryptocurrency sellers exhibit demographic attributes generally associated with less financial sophistication and are more likely to trade in meme stocks. Overall, we provide timely evidence that can inform cryptocurrency policy deliberations by highlighting the characteristics of taxpayers who appear to report cryptocurrency sales.