This study aims to understand the relationship among cryptocurrency, stock, and gold markets. Cointegration, structured VAR, and causality tests were used with daily datasets from 11/09/2017 to 11/17/2023. A cryptocurrency basket is accepted as the cryptocurrency market for this study. The stock markets have a one-way relationship both with the gold and cryptocurrency markets in the short-run. All markets have effects on other markets’ price variances, as well. The price shocks of the markets to each other are not so essential for the prices. However, their own price shocks impact their prices for a few days. The stock market has asymmetric relationships with the gold and cryptocurrency markets. A 1.00 % rise in stock price causes declines in the gold and cryptocurrency prices by 2.35% and 2.42%, respectively. If the gold market or stock market is ignored, a 1.00% rise in gold prices causes a 0.69% rise in cryptocurrency prices, or a 1.00% rise in stock prices raises the cryptocurrency prices by 4.03%.
Cryptocurrency investment is a rapidly growing financial sector, marked by high volatility, decentralized technologies, and significant profit potential. Investors use strategies like long-term holding (“HODLing”), portfolio diversification, and short-term trading. “HODLing” relies on long-term value appreciation but requires resilience to price fluctuations. Diversifying with assets like Bitcoin and Ethereum reduces risk due to their low correlation with traditional investments. The crypto market is highly sensitive to geopolitical, economic, and technological factors, attracting investors during economic instability. Advanced models like LASSO and AutoEncoder aid in price prediction and strategy optimization. Despite high return potential, careful risk management is essential due to volatility and regulatory uncertainty. This study experimentally applies identical cryptocurrency portfolios to different investment strategies, identifying the most profitable approach.
Jonas Gebele, Timm Mutzel, Burak Oez, Florian Matthes
Sealed-bid auctions ensure fair competition and efficient allocation but are often deployed on centralized infrastructure, enabling opaque manipulation. Public blockchains eliminate central control, yet their inherent transparency conflicts with the confidentiality required for sealed bidding. Prior attempts struggle to reconcile privacy, verifiability, and scalability without relying on trusted intermediaries, multi-round protocols, or expensive cryptography. We present a sealed-bid auction protocol that executes sensitive bidding logic on a Trusted Execution Environment (TEE)-backed confidential compute blockchain while retaining settlement and enforcement on a public chain. Bidders commit funds to enclave-generated escrow addresses, ensuring confidentiality and binding commitments. After the deadline, any party can trigger resolution: the confidential blockchain determines the winner through verifiable off-chain computation and issues signed settlement transactions for execution on the public chain. Our design provides security, privacy, and scalability without trusted third parties or protocol modifications. We implement it on SUAVE with Ethereum settlement, evaluate its scalability and trust assumptions, and demonstrate deployment with minimal integration on existing infrastructure.
Cryptocurrency has become a groundbreaking financial innovation, changing the way digital transactions and asset management are handled. Its decentralized structure, reliance on blockchain technology, and potential for worldwide access have attracted a lot of attention from investors, technologists, and policymakers around the globe. However, from an Islamic perspective, the permissibility and ethical issues related to cryptocurrencies need careful review based on Islamic law. Islamic finance is guided by principles from the Quran and Hadith, focusing on justice, transparency, and the prohibition of interest (riba), gambling (maysir), and uncertainty (gharar). Cryptocurrencies, by their nature, challenge traditional financial ideas and raise questions about whether they comply with these principles. Riba (Interest): Unlike traditional banking, cryptocurrencies do not naturally involve interest; however, using them in interest-based deals or speculative trading could go against Islamic teachings. Gharar (Uncertainty): The high volatility and speculative aspect of cryptocurrencies create significant uncertainty, which is discouraged in Islamic finance. Maysir (Gambling): The chance to make profits through speculation and trading in cryptocurrencies can resemble gambling, which is forbidden. Haram Activities: Cryptocurrencies might be used for illegal actions, including money laundering and funding unlawful enterprises, raising ethical worries. Despite these issues, some scholars believe cryptocurrencies can be allowed if used ethically and within Islamic law. They stress the importance of transparency, real economic activity, and avoiding speculation. Also, blockchain technology's potential to support financial inclusion matches Islamic principles of justice and fairness. The Islamic view on cryptocurrencies is complex and multi-layered. While there are real concerns about their volatility, misuse, and speculative nature, there are also chances for ethical and lawful use. It’s important for scholars, financial institutions, and users to work together to create guidelines that make sure cryptocurrencies promote economic growth without breaking Islamic ethical standards. Ongoing research and discussion are key to managing this changing landscape responsibly, ensuring that technological progress aligns with Islam’s moral and legal standards.
Detecting fraudulent transactions in Ethereum is challenging due to the evolving tactics of malicious actors and the complexity of blockchain transactions. This work constructs a proximity-aware graph (PAG) for each Ethereum account, where each node is connected to its transactional neighbours within two hops to capture financial interactions effectively. For better performance, EthAegis integrates both local graphical features and global transactional properties of each proximity-aware graph (PAG).To effectively capture the graphical and transactional relationships between Ethereum accounts, Graph Sample and Aggregate (GraphSAGE) are deployed. It is a Graph Neural Network (GNN) based model that is optimised for inductive learning on large-scale graphs. It is observed that EthAegis could effectively capture hidden patterns and anomalies in Ethereum transactions by considering both the transactional and graphical characteristics. Experimental evaluations on real Ethereum transaction data demonstrate that this method significantly improves fraud detection accuracy while ensuring scalability, providing a robust and adaptive solution to secure blockchain transactions. The proposed model achieves an accuracy of 0.9908, precision of 0.9922, recall of 0.9894, and F1-score of 0.9908 on the Ethereum transactional dataset.
Stanisław Drożdż, Robert Kluszczyński, Jarosław Kwapień, Marcin Wątorek
Multifractality in time series analysis characterizes the presence of multiple scaling exponents, indicating heterogeneous temporal structures and complex dynamical behaviors beyond simple monofractal models. In the context of digital currency markets, multifractal properties arise due to the interplay of long-range temporal correlations and heavy-tailed distributions of returns, reflecting intricate market microstructure and trader interactions. Incorporating multifractal analysis into the modeling of cryptocurrency price dynamics enhances the understanding of market inefficiencies, may improve volatility forecasting and facilitate the detection of critical transitions or regime shifts. Based on the multifractal cross-correlation analysis (MFCCA) whose spacial case is the multifractal detrended fluctuation analysis (MFDFA), as the most commonly used practical tools for quantifying multifractality, in the present contribution a recently proposed method of disentangling sources of multifractality in time series was applied to the most representative instruments from the digital market. They include Bitcoin (BTC), Ethereum (ETH), decentralized exchanges (DEX) and non-fungible tokens (NFT). The results indicate the significant role of heavy tails in generating a broad multifractal spectrum. However, they also clearly demonstrate that the primary source of multifractality are temporal correlations in the series, and without them, multifractality fades out. It appears characteristic that these temporal correlations, to a large extent, do not depend on the thickness of the tails of the fluctuation distribution. These observations, made here in the context of the digital currency market, provide a further strong argument for the validity of the proposed methodology of disentangling sources of multifractality in time series.
A mobilidade urbana representa um dos maiores desafios das cidades contemporâneas, sendo a imprevisibilidade do transporte público um fator crítico que impacta milhões de cidadãos e turistas. Atrasos decorrentes de congestionamentos, acidentes e outros eventos inesperados, somados à complexidade das rotas, comprometem significativamente a experiência do usuário. Este artigo apresenta o SIGRÔ (Sistema Inteligente de Gerenciamento de Rotas de Ônibus), uma solução inovadora para o rastreamento e previsão em tempo real da localização de ônibus coletivos. A arquitetura do sistema baseia-se em uma rede descentralizada Web3, na qual cada veículo atua como um nó comunicante em uma malha peer-to-peer (p2p), utilizando GSM LTE-M e, de forma redundante, LoRa, para mitigar falhas de cobertura. Cada ônibus é equipado com sistemas embarcados dotados de Unidades de Processamento Neural (NPUs), que aplicam Inteligência Artificial para corrigir perdas de sinal de GPS e aprimorar estimativas de chegada, integrando dados históricos e em tempo real. O ecossistema é complementado por um aplicativo multiplataforma (iOS, Android, WebApp e sistema embarcado), que oferece planejamento de rotas, visualização em tempo real, informações sobre paradas e uma interface de gestão para operadores, permitindo o reporte de incidentes. O projeto tem como objetivo aprimorar a pontualidade percebida, otimizar a experiência do usuário e fornecer dados estratégicos para a gestão inteligente do transporte público urbano.
Decentralized storage is one of the most natural applications built on blockchains and a central component of the Web3 ecosystem. Yet despite a decade of active development -- from IPFS and Filecoin to more recent entrants -- most of these storage protocols have received limited formal analysis of their incentive properties. Claims of incentive compatibility are sometimes made, but rarely proven. This gap matters: without well-designed incentives, a system may distribute storage but fail to truly decentralize it. We analyze Shelby -- a storage network protocol recently proposed by Aptos Labs and Jump Crypto -- and provide the first formal proof of its incentive properties. Our game-theoretic model shows that while off-chain audits alone collapse to universal shirking, Shelby's combination of peer audits with occasional on-chain verification yields incentive compatibility under natural parameter settings. We also examine coalition behavior and outline a simple modification that strengthens the protocol's collusion-resilience.
El estudio analizó el comportamiento de las criptomonedas Bitcoin y Ethereum durante el año 2024 mediante la construcción de un modelo estadístico ARIMA (AutoRegressive Integrated Moving Average). La investigación utilizó un enfoque cuantitativo que se dividió en cuatro etapas: recopilación y limpieza de datos históricos, verificación de la estabilidad de los datos, identificación y estimación de los mejores parámetros usando criterios de información, y validación mediante medidas de precisión y análisis de residuos. Los resultados demostraron que el modelo ARIMA fue útil en el pronóstico de valores en mercados estables, destacando su trayectoria en el análisis de datos financieros. Además, los valores bajos de RMSE y MAPE validaron que el modelo tiene la capacidad de realizar pronósticos precisos en escenarios con alta frecuencia. En particular, el MAPE de Bitcoin fue 2,25 % y el de Ethereum 2,85 % durante la etapa de prueba, demostrando que los valores pronosticados tuvieron una ligera desviación con respecto a los reales. No obstante, el modelo puede verse afectado en periodos de alta volatilidad, como en las burbujas especulativas o en los desplomes bursátiles, ya que no tiene la capacidad de adaptarse dinámicamente a cambios súbitos en los parámetros; sin embargo, su utilidad puede mejorar al combinar modelos híbridos con ARIMA.
The CryptoKit research project provides a visual mapping of blockchain technology and Web3 protocols to make them accessible to a wide audience. It includes an open source typeface of more than 200 pictograms of key blockchain terms. When paired with IBM Plex, these icons can be arranged in didactic diagrams thanks to a dedicated tool on this website.
Raaj Anand Mishra, Preeti Bhaskar, M. Hafijul Islam Khan
Purpose Universities worldwide face significant challenges in maintaining administrative data, including security flaws, delays in verification processes and a lack of confidence among those involved. The purpose of this paper is to design an integrated blockchain-based decentralized application architecture for the University of Technology and Applied Sciences (UTAS) in Oman, aligning with Vision 2040’s sustainability goals. Design/methodology/approach The solution uses a hybrid architecture that combines the benefits of the public blockchain with governance at the consortium level appropriate for educational organizations. The user interface layer has role-based dashboards for various stakeholder groups, ensuring proper access control and user experience improvement. The application layer integrates Web3 using the Next.js framework, allowing for seamless interaction between standard Web interfaces and blockchain capabilities. The smart contract layer is made up of eight specialized contracts that handle various administrative responsibilities, each designed with a modular architecture to provide maintainability and upgradeability. The blockchain layer makes use of Ethereum’s proven infrastructure and proof-of-stake consensus, which is dispersed across UTAS’s 13 campuses to ensure decentralization and fault tolerance. Findings This study broadens the architecture by leveraging well-established blockchain frameworks for credential management to include a wide range of educational administrative tasks such as admissions, certifications, alumni management, library services, on-the-job training, examinations and placements across UTAS’s 13 campuses located in 11 governorates. The suggested system makes use of the Ethereum blockchain platform with smart contracts, as well as the InterPlanetary File System for distributed document storage, to ensure immutability, transparency and cost-effective administrative operations. The architecture consists of eight core smart contracts that regulate various administrative duties, five types of stakeholders and a uniform dashboard system that allows seamless data transmission and verification across campuses. Practical implications Key contributions include a practical implementation framework with phased deployment methods, a complete stakeholder governance model and quantitative benefits showing a reduction in processing times and operational cost savings. The architecture’s modular nature allows it to adapt to changing educational requirements while remaining compatible with new technologies such as artificial intelligence and the Internet of Things. Originality/value This research addresses the present limitations of traditional educational administration systems and establishes a framework for the further deployment of blockchain technology in Oman’s higher education sector.
Post-quantum cryptography (PQC) is moving from evaluation to deployment as NIST finalizes standards for ML-KEM, ML-DSA, and SLH-DSA. This survey maps the space from foundations to practice. We first develop a taxonomy across lattice-, code-, hash-, multivariate-, isogeny-, and MPC-in-the-Head families, summarizing security assumptions, cryptanalysis, and standardization status. We then compare performance and communication costs using representative, implementation-grounded measurements, and review hardware acceleration (AVX2, FPGA/ASIC) and implementation security with a focus on side-channel resistance. Building upward, we examine protocol integration (TLS, DNSSEC), PKI and certificate hygiene, and deployment in constrained and high-assurance environments (IoT, cloud, finance, blockchain). We also discuss complementarity with quantum technologies (QKD, QRNGs) and the limits of near-term quantum computing. Throughout, we emphasize crypto-agility, hybrid migration, and evidence-based guidance for operators. We conclude with open problems spanning parameter agility, leakage-resilient implementations, and domain-specific rollout playbooks. This survey aims to be a practical reference for researchers and practitioners planning quantum-safe systems, bridging standards, engineering, and operations.
Abstrak - Tingginya volatilitas Bitcoin mendorong kebutuhan model prediktif presisi untuk landasan keputusan investasi optimal. Studi ini mengimplementasikan algoritma Random Forest guna memprediksi pergerakan harga berdasarkan 1.766 data historis harian (Januari 2020-Oktober 2024). Pra-pemodelan diawali analisis korelasi Pearson dengan ambang batas 0.5, yang menyeleksi fitur High (0,999), Open (0,998), dan Low (0,997) sebagai prediktor akibat asosiasi kuat, sementara Volume dan Change% dieliminasi karena kontribusi minimal. Pengujian membandingkan dua strategi pembagian data: partisi acak dan tidak acak (rasio 80:20), menggunakan metrik Mean Absolute Percentage Error (MAPE) dan Akurasi. Hasil empiris menunjukkan partisi acak unggul (MAPE 1,34%; Akurasi 98,66%) dibanding partisi tidak acak (MAPE 1,7%; Akurasi 98,3%). Konklusi menegaskan efektivitas signifikan algoritma Random Forest, dengan keberhasilan bergantung pada ketepatan seleksi fitur dan adaptasi strategi pembagian data terhadap karakteristik dataset.Kata kunci: Bitcoin; Random Forest; Prediksi Harga; Korelasi Pearson; MAPE; Abstract - The high volatility of Bitcoin necessitates precise predictive models for optimal investment decision-making. This study implements the Random Forest algorithm to predict price movements based on 1,766 daily historical data points (January 2020 - October 2024). Pre-modeling began with Pearson correlation analysis with a threshold 0.5, which selected the High (0.999), Open (0.998), and Low (0.997) features as predictors due to their strong association, while Volume and Change% were eliminated due to their minimal contribution. The testing compared two data splitting strategies: random and non-random (80:20 ratio), using the Mean Absolute Percentage Error (MAPE) and Accuracy metrics. Empirical results showed that random partitioning outperformed non-random partitioning (MAPE 1.34%; Accuracy 98.66% compared to MAPE 1.7%; Accuracy 98.3%). The conclusion confirms the significant effectiveness of the Random Forest algorithm, with success depending on the accuracy of feature selection and adapting the data splitting strategy to the characteristics of the dataset. Keywords: Bitcoin; Random Forest; Price Prediction; Pearson Correlation; MAPE;
Smart contracts, a revolutionary technology that offers a digital alternative to conventional contracts, are popular. Smart contracts also known as automated digital contracts are becoming common in various countries due to their efficiency and openness. Various national and global forums have agreed that smart contracts might alter contract enforcement and boost economic development in India. Given this, it’s crucial to understand the Indian Contract Act, (ICA) 1872 stance on smart contracts. ICA requires testing smart contracts for contractual validity before entering the uncharted seas of autonomous and anonymous digital contracting. This experiment raises many issues, especially given the law’s strict procedural structure. This article refutes the claim that smart contracts should be regulated by self-regulation. Rather author prefers a broad interpretation of substantive contractual law to harmonize smart contracts under the ICA, following common law’s flexibility. It is shown that smart contracts are built on the same principles as common law contracts and deepen our research in the framework of Indian law and precedent. Similar approaches from other countries support this perspective. Although many legislations require change, it is believed that a smart contract law is not needed. The paper concludes by proposing solutions to the potential obstacles that may arise due to present approach.
Rooftop solar (RTS) represents a critical component of India’s clean energy transition, offering decentralized generation, reduced transmission losses, and potential resilience benefits. Yet, despite ambitious national targets and substantial technical potential, RTS adoption has lagged behind expectations. This narrative review synthesizes peer-reviewed literature (2019–2025), government program documents, and policy reports to examine the trends, barriers, enablers, economics, regional signals, stakeholder outcomes, and policy implications shaping rooftop solar adoption in India. Findings indicate that commercial and industrial consumers have historically dominated the sector due to favorable tariffs and access to credit, while residential uptake accelerated only after the launch of flagship initiatives such as PM Surya Ghar. Persistent barriers include high upfront costs, affordability gaps, regulatory uncertainty, procedural delays, information asymmetries, and built environment constraints. At the same time, innovations such as simplified subsidy pipelines, digitalized approval portals, DISCOM performance incentives, vendor certification, and emerging business models including RESCO/OPEX and group or virtual net metering demonstrate viable pathways to expand adoption. The review identifies future research needs in program evaluation, financial innovation, grid integration, apartment governance, and quality assurance, and emphasizes the importance of stable regulatory frameworks, inclusive finance, and community-oriented models.
The unprecedented growth of digital art in the contemporary creative economy has empowered artists to reach global audiences, yet it has simultaneously amplified threats of copyright infringement, piracy, and unauthorized duplication. Traditional intellectual property frameworks, while legally robust, are often ill-suited to address the speed, borderless nature, and technological complexity of digital content circulation. Blockchain technology emerges as a transformative paradigm, introducing decentralized and tamper-proof mechanisms for digital rights management. Through non-fungible tokens (NFTs), smart contracts, and immutable ledgers, blockchain provides verifiable proof of authorship, facilitates transparent provenance tracking, and automates royalty distribution without reliance on intermediaries. This manuscript critically examines the role of blockchain in strengthening copyright protection for digital artists by combining an extensive review of existing literature with statistical survey data drawn from practicing artists across multiple regions. Findings reveal that while blockchain adoption is gaining momentum, barriers such as regulatory uncertainty, high transaction costs, energy inefficiency, and limited user literacy constrain large-scale implementation. The study demonstrates that blockchain can enhance creative autonomy, ensure fair economic participation, and foster trust in digital art ecosystems, but its success depends on legal integration, sustainable infrastructure, and artist-centered governance. This research contributes to the discourse by offering a multi-layered framework for blockchain-enabled copyright systems, bridging technological innovation with socio-legal realities, and outlining directions for future policy and research in intellectual property protection.
Yanjing Ren, Jia Zhao, Jingwei Li, Patrick P. C. Lee
Blockchains have revolutionized trust and transparency in distributed systems, yet their heavy reliance on key-value (KV) storage for managing immutable, rapidly growing data leads to performance bottlenecks due to I/O inefficiencies. In this paper, we analyze Ethereum’s storage workload traces, with billions of KV operations, across four dimensions: storage overhead, KV operation distributions, read correlations, and update correlations. Our study reveals 11 key findings and provides suggestions on the design and optimization of blockchain storage.
Xihan Xiong, Zhipeng Wang, Qin Wang, William Knottenbelt
Decentralized communication is becoming an important use case within Web3. On Ethereum, users can repurpose the transaction input data field to embed natural-language messages, commonly known as Input Data Messages (IDMs). However, as IDMs gain wider adoption, there has been a growing volume of toxic content on-chain. This trend is concerning, as Ethereum provides no protocol-level support for content moderation. We propose two moderation frameworks for Ethereum IDMs: (i) BUILDERMOD, where builders perform semantic checks during block construction; and (ii) USERMOD, where users proactively obtain moderation proofs from external classifiers and embed them in transactions. Our evaluation reveals that BUILDERMOD incurs high block-time overhead, which limits its practicality. In contrast, USERMOD enables lower-latency validation and scales more effectively, making it a more practical approach in moderation-aware Ethereum environments. Our study lays the groundwork for protocol-level content governance in decentralized systems, and we hope it contributes to the development of a decentralized communication environment that is safe, trustworthy, and socially responsible.
Dini Rohmayani, Ilham Alfath, Castaka Agus Sugianto
Abstrak - Implementasi Non-Fungible Token (NFT) sering menghadapi masalah permanensi data karena ketergantungan pada penyimpanan terpusat yang rentan terhadap penghapusan dan perubahan. Penelitian ini mengembangkan aplikasi web berbasis Decentralized Application (DApp) untuk pembuatan Non-Fungible Token (NFT) yang mengintegrasikan InterPlanetary File System (IPFS) dengan Smart Contract ERC-721 pada blockchain Ethereum. Metode pengembangan menggunakan pendekatan waterfall dengan implementasi React.js dan Next.js untuk frontend serta Solidity untuk smart contract. Sistem dirancang dengan arsitektur three-tier yang memfasilitasi pembuatan koleksi Non-Fungible Token (NFT) melalui kontrak Factory dan pengelolaan token melalui NFTCollection, dengan metadata dan aset digital disimpan menggunakan Content Identifier (CID) pada InterPlanetary File System (IPFS). Pengujian blackbox menunjukkan seluruh fungsi sistem berjalan sesuai spesifikasi, sementara User Acceptance Testing (UAT) dengan 24 responden menghasilkan tingkat penerimaan 90%. Hasil penelitian membuktikan bahwa integrasi InterPlanetary File System (IPFS) dengan smart contract ERC-721 dapat mengatasi permasalahan permanensi metadata dan aset digital, sekaligus menyederhanakan proses minting Non-Fungible Token (NFT) bagi pengguna non-teknis melalui antarmuka yang intuitif.Kata kunci: Non-Fungible Token (NFT); ERC-721; IPFS; Kontrak Pintar; Blockchain; Abstract - Podo Practical implementations of Non-Fungible Tokens (NFTs) often face data permanence issues due to reliance on centralized storage systems vulnerable to deletion and modification. This research develops a web-based Decentralized Application (DApp) for NFT creation that integrates the InterPlanetary File System (IPFS) with ERC-721 Smart Contracts on the Ethereum blockchain. The development methodology employs a waterfall approach with React.js and Next.js for frontend implementation and Solidity for smart contracts. The system is designed with a three-tier architecture facilitating NFT collection creation through the NFTFactory contract and token management through NFTCollection, with metadata and digital assets stored using Content Identifiers (CID) on IPFS. Black box testing demonstrates that all system functions operate according to specifications, while User Acceptance Testing (UAT) with 24 respondents yields an acceptance rate of 90%. The research findings prove that integrating IPFS with ERC-721 smart contracts addresses metadata and digital asset permanence issues while simplifying the NFT minting process for non-technical users through an intuitive interface.Keywords: Non-Fungible Token (NFT); ERC-721; IPFS; Smart Contract; Blockchain;
The rapid expansion of digital assets has created a conflict between technological innovation and environmental, social, and governance (ESG) principles, particularly concerning the energy consumption of legacy consensus mechanisms. This has led to the emergence of "sustainable" cryptocurrencies, raising the critical question of whether the market financially rewards sustainability. This study quantitatively investigates the existence and magnitude of an "ESG premium" in the digital asset market. A quasi-longitudinal study was conducted on a panel dataset of 20 cryptocurrencies (10 sustainable, 10 traditional) from January 1, 2021, to December 31, 2024. A detailed, transparent composite ESG score was developed to measure sustainability. The primary analysis utilized a panel data fixed-effects regression model to assess the relationship between asset prices and ESG scores, controlling for market capitalization, trading volume, market-wide indices, and key technological factors like protocol age, scalability, and developer activity. To address endogeneity and validate causality, we employed models with lagged independent variables. Further robustness checks were performed across bull and bear market sub-periods. A GARCH (1,1) model was used to analyze differences in price volatility. The primary regression model reveals a statistically and economically significant positive relationship between ESG scores and cryptocurrency prices. A 10-point increase in the ESG score is associated with a 4.1% price premium (b=0.0041, p < 0.001), even after controlling for technological modernity. This finding remains robust in models using lagged variables and across different market cycles. GARCH analysis confirms that sustainable cryptocurrencies exhibit significantly lower price volatility. In conclusion, the findings provide strong, robust empirical evidence for a persistent ESG premium in the cryptocurrency market. This suggests that investors price in the perceived long-term viability, reduced risk profile, and ethical alignment of sustainable assets, signaling a maturation of the market where non-financial, sustainability-focused metrics are integral to asset valuation.
Cryptocurrency money-laundering forensic analysis after Web3 incidents faces challenges such as fragmented evidence, expanding transaction paths, and cross-chain discontinuity. Existing Web3 AML methods largely rely on manual clues and heuristic or graph-search-based tracing, with outputs limited to lists of suspicious addresses and lacking path-level evidence and verifiable explanations. Directly applying general-purpose large language models to raw transaction flows also struggles to ensure evidence constraints and result verifiability. To address these limitations, this paper presents RISKTAGGER, an LLM-guided agent for forensic tracing of Web3 cryptocurrency money laundering. RISKTAGGER embeds the LLM as an evidence-constrained decision component within a controlled tracing loop. It extracts case clues from public incident materials, recursively expands a risk-labeled fund-flow graph over on-chain evidence, and generates evidence-organized reports for analyst review. We evaluate it on five real-world incidents spanning multiple years and covering heterogeneous attack patterns and laundering path structures. We further conduct cross-case generalization analysis, baseline comparison, component ablation, and LLM backend analysis. In the main Bybit case, the system achieves a 97.33% address recall and a 98.69% expert-reviewed sampled address precision. Across the other four incidents, it achieves 95.24-100.00% address recall and 91.27-100.00% expert-reviewed address precision. The cross-case results further show that the complexity of Web3 money laundering arises from heterogeneous mechanisms, including short-cycle fund fragmentation, long-range laundering paths, interwoven DeFi services, and deterministic denomination splitting. RISKTAGGER can recover case-related fund paths, identify high-priority risk accounts, and organize public evidence into verifiable forensic reports.
Global supply chains face increasing disruptions from cyber threats, geopolitical instability, extreme weather events, and a range of economic, social, and environmental sustainability challenges. As these disruptions intensify, enhancing Supply Chain Resilience (SCR) has become a strategic priority. This study investigates how Distributed Ledger Technology (DLT) can contribute to SCR by mitigating vulnerabilities and strengthening key capabilities within global supply chains. A qualitative research approach is employed, utilizing expert evaluations to examine DLT’s impact on supply chain vulnerabilities and capabilities. Five workshops were conducted with 25 industry professionals from logistics, IT, procurement, and risk management. Experts examined how DLT could address disruptions stemming from supplier instability, poor traceability, and regulatory and environmental pressures, while highlighting its potential to drive ethical sourcing and environmentally responsible practices. The structured discussions were guided by theoretical frameworks and expert evaluations were synthesized into two analytical matrices illustrating DLT’s influence on SCR. The findings reveal that the contribution of DLT to SCR and sustainability is highly context-dependent, with its effectiveness hinging on how it is embedded within governance structures and aligned with the interplay of complementary technologies. Building on these insights, the study presents the DLT-LFL (Distributed Ledger Technology–Learning Feedback Loop) framework, which integrates sensing, decision-making, adaptation, and predictive learning from distributed operational data, allowing supply chains to better anticipate disruptions, adjust processes dynamically, and continuously strengthen resilience and sustainable practices. The study also develops a practical checklist to assess how effective DLT applications and their integration with predictive and AI-driven analytics reduce vulnerabilities, strengthen capabilities, mitigate risks, and support adaptive decision-making.
Smart contract adalah program yang dapat memastikan bahwa aturan atau perjanjian di jaringan basis data terdistribusi berlaku untuk transaksi yang terjadi. Penelitian ini adalah penelitian hukum yuridis normatif dengan sifat penelitian deskriptif. Teknik pengumpulan data dilakukan melalui studi kepustakaan. Analisis dalam penelitian ini dilakukan secara kualitiatif. Berdasarkan hasil penelitian ditemukan bahwa pengaturan mengenai smart contract di Indonesia belum diatur secara jelas dalam suatu regulasi. Smart contract dapat diterapkan di Indonesia asalkan sesuai dengan hukum dan tidak melanggar norma-norma sosial. Keabsahan hukum atas kehadiran smart contract dikaitkan dengan transaksi elektronik memerlukan kerangka hukum yang jelas dan dukungan dari berbagai pihak, sebab regulasi mengenai smart contract di Indonesia masih belum sepenuhnya terdefinisi. Sehingga kepastian hukum terhadap keabsahan hukum atas kehadiran smart contract belum dapat diwujudnya sepenuhnya, dikarenakan sandungan dalam regulasi yang belum jelas. Implementasi smart contract pada teknologi blockchain dalam kaitannya dengan praktik Notaris sebagai pejabat umum tidak dapat sepenuhnya menghapuskan peran Notaris selaku pejabat umum yang diberikan wewenang oleh ketentuan UUJN.