Tanishka Ahire, Jyotsana Bagul, Dr. Archana Bendale
Abstract: The idea of cryptocurrency is really interesting. It started as a money idea and now it is changing how the world thinks about money and technology. Cryptocurrency began with Bitcoin in 2008. Now it includes ideas like blockchain and special kinds of contracts. There are also kinds of money from central banks and unique digital things called NFTs. This paper looks closely at the technology behind cryptocurrency. How it affects the economy, people and laws. It talks about the things that cryptocurrency can do which will probably help it grow. It also talks about the problems that cryptocurrency is facing which might slow it down. The paper looks at what might happen with cryptocurrency in the future and how it will affect the world and money systems. After looking at a lot of research from 2008 to 2023 it seems that cryptocurrency is a concept that could be really big, in the future. For it to really work some technical and other issues need to be figured out. Cryptocurrency has to deal with these issues to be sustainable. The idea of cryptocurrency is still very promising. It needs to solve some problems.. Keywords: Cryptocurrency, Blockchain Technology, Decentralized Finance (DeFi), Smart Contracts, Consensus Mechanisms
Bitcoin research increasingly relies on on-chain indicators to study network activity, monetary issuance, transaction demand, miner incentives, coin-age behavior, and long-run monetary dynamics. However, many commonly used Bitcoin metrics are dispersed across commercial platforms, subject to heterogeneous definitions, or not fully reproducible from primary blockchain data. This manuscript introduces Open Bitcoin Metrics (OBM), a reproducible, full-node-derived dataset and reference guide for Bitcoin on-chain time series designed for economic and econometric research. The dataset provides documented daily series covering block production, block-space usage, transaction counts, supply, issuance, fees, miner revenue, mining difficulty, estimated hashrate, Bitcoin Days Destroyed, dormancy, liveliness, UTXO counts, spent output value, and related UTXO-age indicators. Metrics are reconstructed from a locally maintained Bitcoin Core full node, a persistent spent-output indexer, or deterministic transformations of previously generated OBM series. Each series is accompanied by open-source Python code, stable identifiers, explicit definitions, metadata, validation procedures, interpretive caveats, and comparisons with the closest publicly available metrics. The dataset is intended to support transparent empirical research, replication, teaching, and comparative analysis across monetary economics, financial economics, and blockchain studies.
Shah Nawaz Haider, Steve Austin, Arnab Barua, Sarowar Morshed Shawon · 5 authors
Time-series forecasting supports decisions in finance, en-ergy, transportation, public health, and industrial monitoring. Recent foundation models improve transfer across forecast-ing tasks, but many depend on centralized data and Trans-former attention, which restricts their use for long, high-di-mensional, and privacy-sensitive signals. This paper presents QuantFlow, a probabilistic forecasting framework that com-bines inverted sequence embedding, bidirectional Mamba state-space decoders, quantile regression, and federated learning. Each variable is embedded over the complete ob-servation window, processed in forward and reverse direc-tions, and projected to five conditional quantiles. TSMixup expands temporal diversity through Dirichlet-weighted inter-polation while preserving sequence structure. Experiments cover cryptocurrency, traffic, electricity, Electricity Trans-former Temperature, influenza, and weather data. QuantFlow obtains mean squared errors of 0.2834 on ETTm1 and 0.2218 on Weather, and a 20-client non-IID deployment retains use-ful accuracy after three communication rounds without cen-tralizing raw records. The results indicate that selective state-space modelling is a promising basis for scalable, uncer-tainty-aware, and privacy-conscious time-series prediction, while also revealing limitations on irregular epidemiological signals and long-horizon generalization.
Our study examines the impact of climate policy uncertainty on the volatility of Bitcoin, Ethereum and Litecoin. Using monthly Climate Policy Uncertainty Index data from 2010 to 2024, we forecast daily cryptocurrency volatility with a GARCH-MIDAS model. The results show that higher climate policy uncertainty significantly increases volatility across all three cryptocurrencies over the full sample period. Out-of-sample analysis, which captures structural changes in energy consumption, reveals stronger effects for Bitcoin. Ethereum shows insignificant responses following its transition to a proof-of-stake mechanism, while Litecoin exhibits a significant positive relationship with uncertainty. Overall, climate policy uncertainty proves to be a strong predictor of cryptocurrency volatility, particularly for energy-intensive assets. The findings highlight the importance of policy-related information in shaping investor behaviour in crypto markets and provide useful implications for cryptocurrency issuers, retail investors and portfolio managers seeking to manage risk under changing regulatory and environmental conditions.
Abstract Bitcoin was the breakthrough innovation demonstrating peer-to-peer transfer of value without a central bank and has since expanded to countless innovations such as smart contract applications, decentralized finance protocols and asset tokenization. The EU is moving from scattered state-specific rules governing cryptocurrency activities to a coherent European regulatory regime. This paper review the transition to a harmonized framework in 2024-2025 from a doctrinal-institutional perspective, unpack how to carry out the three main legislative instruments: MiCA, TFR on information accompanying transfers of funds and transfers of certain crypto-assets and amending the EU directive and the EU AML package . Moreover, I look at the implications of DAC8 for the tax treatment of crypto-assets and tokenized assets. In 2025, the market begins institutionalizing, as MiCA requires significant compliance measures in terms of governance, transparency and conduct for CASPs to get licensed. Moreover, in conjunction with the new TFR rules, compliance for CASPs, at least in the business models discussed, effectively transforms into an operational infrastructure issue revolving around data quality, process efficiency and interoperability. By way of comparison, I analyze eight example business models in eight representative EU markets that appear to be impacted. These include: two major exchanges, two broker-dealers offering cryptocurrency on trading platform, a provider of non-custodial software wallets, two DeFi protocol participants and two NFT platform providers. These fall into three general categories depending on their legal status, direct regulatory burden and level of engagement with decentralized technologies. Finally, harmonized regulatory frameworks like the one outlined for the EU increase operational fixed costs and favor consolidation, reduce the benefits for regulatory arbitrage and thereby boost user protection, although part of innovation may pivot towards B2B solutions.
Numerous reports and studies indicate that the lack of effective regulation in cryptocurrencies has not only led to substantial financial losses but also eroded the traditional ”central bank-commercial bank” framework, thereby destabilizing financial systems. To address these issues, a growing body of research has focused on developing regulatory mechanisms for cryptocurrencies. However, existing regulatory proposals face a persistent trilemma: they fail to simultaneously achieve three critical properties—(i) one‑time registration with self‑updating addresses, (ii) completeness (including a lost‑coin retrieval mechanism), and (iii) fine‑grained access control that respects the ”central bank‑commercial bank” framework. This study bridges this gap by proposing TCoin, the first regulatory cryptocurrency that fulfills all three requirements. We first introduce TSFG, a traceable scheme built on SkyEye, which employs cryptographic techniques to achieve one‑time registration with self‑updating addresses and fine‑grained access control for tracing. By integrating TSFG into the RSCoin framework, we construct TCoin—a regulatory cryptocurrency that achieves one‑time registration with self‑updating addresses, ensures completeness through a novel coin recovery mechanism, and enforces fine‑grained access control. Compared to prior work (CB, DAP, PDC, RSCoin, e‑CNY, and RECoin), TCoin is the first to resolve the regulatory trilemma, offering a comprehensive solution that reconciles the disruptive potential of cryptocurrencies with the stability requirements of the traditional monetary system.
Abstract Smart contracts are the fundamental building block of decentralized applications (DApps) and decentralized finance (DeFi). However, their immutability makes security flaws exceptionally costly. Despite advancements in vulnerability detection, such as static and dynamic analysis, formal verification, and Solidity language improvements, vulnerabilities continue to result in substantial financial losses, exceeding $2 billion in 2024 alone. This paper presents a comprehensive analysis of smart contract vulnerabilities derived from real-world exploits, systematically categorized into seven distinct types. Each category is illustrated with Solidity code examples and insights from notable exploits. An Enhanced test suite is developed by restructuring the existing solidity-defects-and-bugs suite and supplementing it with new smart contract implementations to address underrepresented vulnerabilities, including flash loan and price oracle manipulation. We evaluate three widely used analysis tools (Slither, Mythril, and 4naly3er) on both the original and Enhanced suites, revealing substantial limitations in detection coverage. To address these limitations, we introduce the Solidity Defects and Bugs Analysis (SDABA), which incorporates advanced analyses and detectors to identify 28 vulnerability variations across both suites. Results on the SDB and Enhanced test suites show that SDABA improves overall precision, recall, and F1-score compared with the evaluated tools. Finally, we release the source code, test suite, and vulnerability reports to support future research in smart contract security.
Cryptocurrency regulation faces a fundamental mismatch between static rules and rapidly transforming markets. We demonstrate that Bitcoin alternates between bounded and unbounded price regimes, requiring adaptive rather than uniform regulatory frameworks. Using extreme value theory on over a decade of Bitcoin data, we show that tail risk characteristics switch between finite-limit and heavy-tailed regimes, with profound implications for investor protection, capital requirements, and systemic risk management. Traditional approaches either overregulate during stable periods or underprotect during volatile regimes. We propose regime-contingent regulatory frameworks that automatically adjust oversight intensity based on statistical detection of tail risk characteristics. Backtesting over 2016–2025 demonstrates that the adaptive framework reduces average capital requirements by 79% overall and by 84% during bounded regimes while escalating protections before major crashes, outperforming static Basel III-style rules. Robustness analyses across multiple window lengths (90, 180, 365, and 730 days), thresholds, and bootstrap specifications confirm that regime-switching is a persistent structural feature of Bitcoin markets. Implementation requires international coordination, transparent methodology, and clear adjustment protocols.
Since the first implementation of a blockchain with Bitcoin in 2009, cryptoassets created and transacted using blockchain technologies have grown and diversified significantly. Because regulatory regimes, which govern cryptoassets, do not have global coverage, criminal actors find opportunities to commit cryptoasset fraud. While it can be difficult to distinguish between cryptoassets that are honest but high risk and cryptoassets that are outright fraudulent, investors seeking significant returns frequently invest in unregulated cryptoassets, namely cryptocurrencies and non-fungible tokens (NFTs). This study provides a crime script analysis to examine the chronological and functional steps offenders use to execute cryptoasset fraud. It considers three types of crypto asset fraud and how they have functioned over time: Ponzi schemes, cryptoasset exit scams, such as cryptocurrency “rug pulls,” and NFT “mint-and-run” schemes, where invested value is stolen from a crypto asset project. By outlining the fundamental crime script of cryptoasset fraud, this study considers the implications for regulators. Of note, this study shows that while the stages of cryptoasset frauds are consistent, the speed at which frauds are executed has, on average, increased significantly. This rapidity of execution provides enduring challenges to regulators, who often cannot respond quickly. This challenge must be considered if regulation is to be effective.
The purpose of the research is to explore the latest trends in blockchain and cryptocurrency adoption. Cryptocurrency has been drawing the attention of individual investors. Although institutional investors had been hesitant to invest in cryptocurrencies due to lack of clarity regarding regulations, recent legislation encouraged them to add cryptocurrency to their investment portfolios. However, blockchain the underlying technology of cryptocurrency, has also drawn the attention of both companies and researchers. The aim of this study is to identify the latest trends through an analysis of publications on blockchain and cryptocurrency adoption. To achieve that, the study adopts a bibliometric approach by using both VOSviewer and Bibliometrix programs after obtaining the required dataset from Web of Science (WOS). The results exhibit the latest trends as well as both qualitative and quantitative statistics, such as the growth rate, density and relations among different studies on the subject.
Liu Hong Yuan Tom, Ruilin Wang, Hairui Wang, Ziqi Cao · 5 authors
This study examines the impact of social media sentiment on Bit-coin market volatility. While existing literature often relies on single-source data or isolated factors, this research introduces a novel three-source pricing framework that integrates Twitter-derived social media sentiment, investor leverage ratios, and historical market data. Using a Weighted Least Squares (WLS) regression model to address heteroscedasticity in financial time series, we analyze daily Bitcoin returns from 2021 to the first half of 2022. Our results indicate that both social media sentiment has a statistically significant positive effect on Bitcoin returns. The model successfully identified high-risk market conditions, as validated by the May-June 2021 crash. These findings demonstrate that social media sentiment has a huge impact on cryptocurrency markets.
Deepak Gupta, Temur Eshchanov, Jabbarov Umarbek, Berdiyev Anvar Abduraxmanovich · 6 authors
The global halal industry faces critical challenges in ensuring product authenticity, supply chain transparency, and consumer trust. This chapter examines the transformative role of artificial intelligence (AI) technologies in revolutionizing halal product verification and market analysis. Through comprehensive analysis of machine learning, computer vision, blockchain integration, and advanced analytical techniques, we explore how AI-driven solutions address authentication challenges, detect adulteration, and enhance traceability across halal supply chains. The chapter synthesizes current research on deep learning applications for food fraud detection, spectroscopic analysis coupled with chemometrics, DNA barcoding for species identification, and distributed ledger technologies for certification management. We present frameworks for implementing AI-powered verification systems, discuss technological barriers and opportunities, and propose strategic recommendations for stakeholders.
Although the legal status of digital assets has received attention in various previous studies, research that specifically discusses the authority and responsibility of notaries in preparing inheritance certificates related to digital assets within the framework of Western inheritance law in Indonesia remains limited. This study aims to analyze the legal position of digital assets, particularly cryptocurrency and Non-Fungible Tokens (NFTs), as objects of inheritance under inheritance law in Indonesia, and to examine the authority and limits of notarial responsibility in preparing inheritance certificates related to digital assets. This study used a normative legal research method with statutory, conceptual, and analytical approaches. Primary, secondary, and tertiary legal materials were collected through library research and analyzed qualitatively, supported by interviews with notarial practitioners. The results show that digital assets with economic value can be classified as intangible movable objects based on Articles 499, 503, and 504 of the Indonesian Civil Code, and therefore may form part of an estate. However, notarial authority is limited to formal aspects, namely the verification of identity, documents, and statements of the appearers, and does not include guaranteeing access to or the transfer of digital assets, which depend on private keys and digital platform policies. Notarial responsibility is limited to formal truth, not material truth regarding the existence, ownership, or accessibility of digital assets. The conclusion of this study emphasizes the importance of comprehensive regulations and standard operating procedures for notaries in handling the inheritance of digital assets. These findings contribute to the development of notarial law in addressing technological challenges and broaden the understanding of the adaptation of inheritance law to digital assets. The implications of this study include theoretical contributions to the literature on notarial law and inheritance law, as well as practical recommendations for the Indonesian Notary Association and policymakers to formulate clear guidelines on the inheritance of digital assets.
Understanding Proof-of-Work in Blockchain: Foundations, Security, and Limitations Keywords: Blockchain, Consensus, Proof-of-Work, Cryptographic Hash, Cryptography, 51% Attack. 1. Introduction In traditional distributed systems, such as banking databases, a central authority determines transaction validity. In contrast, decentralized networks like Bitcoin lack a central server, allowing unrestricted participation. This structure introduces two significant challenges:This results in two critical challenges: 1. The Byzantine Generals Problem: How do independent nodes agree on a single history of data if some nodes are malicious or untruthful? 2. Sybil Attacks: What stops an attacker from creating 10 million fake virtual nodes to vote and overpower honest nodes? Proof-of-Work (PoW) addresses both challenges. Instead of assigning one vote per identity, which is susceptible to falsification, PoW allocates voting power according to computational resources, which require significant hardware and energy investment. 2. The Core Mechanics: How Mining Actually Works Mining functions as a network-wide lottery, where the probability of success is proportional to computational speed. The process begins with solving a cryptographic puzzle. 2.1 The Cryptographic Puzzle A block consists of a batch of transactions, the hash of the previous block, and a field called a nonce (number used once). Miners repeatedly modify the nonce until the hash of the entire block matches a specific pattern.Specifically, the resulting hash must be less than or equal to a predetermined target value. +---------------------------------------------------------+ | BLOCK HEADER | | [Prev Hash] + [Merkle Root (TXs)] + [Timestamp] + [Nonce] | +---------------------------------------------------------+ | v SHA-256 Hashing | v Is the Hash < Target Threshold? / \ YES NO / \ [Success! Broadcast Block] [Increment Nonce & Try Again] Because SHA-256 is a cryptographic hash function, it has two key properties: Pre-image Resistance (One-Way): You cannot reverse-engineer a hash. If I give you a hash output, you cannot calculate the input. Avalanche Effect: Changing just one bit in the nonce completely alters the final hash output unpredictably. As a result, no mathematical shortcut exists for determining the correct nonce. Miners must use brute-force computation, generating billions of hashes per second (hash rate) until a valid solution is identified (Hash Rate — Measuring Bitcoin's Mining Power, 2026). Once a solution is found, the miner broadcasts the block, and other nodes verify it instantly with a single hash calculation, illustrating computational asymmetry. This mechanism maintains the network's equilibrium. 2.2 Difficulty Adjustment When additional miners join the network, the aggregate hash rate increases, resulting in faster block discovery. To maintain consistent block times, the protocol automatically adjusts the target threshold.If blocks are being found faster than the target time (e.g., 10 minutes in Bitcoin), the target number decreases. A smaller target means the hash must start with more leading zeros, making it statistically harder to guess. 3. Security Framework: The Rules of Engagement PoW operates on the economic principle that securing the network should be more profitable than attacking it. The following rule defines the network's dispute resolution mechanism. 3.1 The Longest Chain Rule If two miners simultaneously discover valid blocks, the network temporarily splits into two branches, known as a fork. Nodes resolve this by following the longest chain, which is defined as the branch with the greatest accumulated proof-of-work, thus maintaining a unified transaction history. [Block 101] ---> (Orphaned / Dropped) / ---- [Block 100] --+ \ [Block 101] ---> [Block 102] <--- Longest Chain (Accepted) 3.2 The 51% Attack If an attacker manages to control more than 50% of the network’s total computing power, they can out-mine the honest portion of the network.An attacker may mine a private chain in secret, spend coins on the public chain, and later broadcast the longer private chain. According to the longest chain rule, the network accepts the attacker's version of history, thereby invalidating transactions on the honest chain. This scenario, known as a Double-Spend Attack, highlights a significant vulnerability and contributes to ongoing criticism of PoW despite its security advantages. 4. Why the Industry is Moving Away from PoW While PoW is incredibly secure, it has two major flaws that make it difficult to scale for modern applications. 4.1 The Scalability Problem In PoW systems, each full node must process and store every transaction for verification. Due to limited block sizes and intentionally high block times to prevent network desynchronization, transaction throughput remains low. For example, Bitcoin processes approximately 7 transactions per second (TPS), whereas Visa handles thousands of TPS. 4.2 Energy Consumption Miners compete to achieve the highest hash rate by continuously operating large-scale data centers equipped with specialized hardware (ASICs). This process consumes substantial amounts of electricity, comparable to the consumption of a medium-sized country, and results in significant environmental impact. 5. Conclusion Proof-of-Work constituted a significant advancement in computer science by linking digital consensus to physical resource constraints, particularly energy. This innovation demonstrated the feasibility of decentralized trust. However, due to limited throughput and substantial energy requirements, newer blockchain networks increasingly adopt alternative consensus mechanisms, such as Proof-of-Stake (PoS), where voting power is determined by cryptocurrency holdings rather than energy expenditure. References Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. (The original whitepaper). Eyal, I., & Sirer, E. G. (2014). Majority is not enough: Bitcoin mining is vulnerable. (Introduced the concept of Selfish Mining). Narayanan, A., et al. (2016). Bitcoin and Cryptocurrency Technologies. Princeton University Press. (An excellent foundational textbook for CS students). (2026). Hash Rate — Measuring Bitcoin's Mining Power. Bitcoin Notes Online. https://www.bitcoinnotesonline.com/learn/hash-rate
Serving as the first touch point for users to the cryptocurrency world, cryptocurrency wallets allow users to manage, receive, and transmit digital assets on blockchains and interact with emerging decentralized finance (DeFi) applications. Unfortunately, cryptocurrency wallets have always been the prime targets for attackers, and incidents of wallet breaches have been reported from time to time. Although some recent studies have characterized the vulnerabilities and scams related to wallets, they have mostly been studied at a coarse granularity, overlooking potential risks inherent in detailed designs of cryptocurrency wallets, especially from perspectives including user interaction and advanced features. To fill the void, in this paper, we present a fine-grained security analysis of browser-based cryptocurrency wallets. To pinpoint security issues in wallet components, we design WalleTruth, a visual-oriented testing framework specifically for browser-based wallet extensions. We have identified 12 attack vectors that can be abused by attackers to exploit cryptocurrency wallets and exposed 21 concrete attack strategies. By applying WalleTruth on 39 widely-adopted browser-based wallet extensions, we find that all of them can be abused to steal crypto assets from innocent users. Identified potential attack vectors were reported to developers in a timely manner and 26 issues have been patched already. This calls for urgent action from the community to mitigate threats related to cryptocurrency wallets.
Backdoor attacks on Ethereum smart contracts are a kind of attack in which an adversary exploits the privileges of his/her developed smart contract to manipulate the cryptoassets generated by that contract. Although there are several countermeasures against backdoor attacks, to the best of our knowledge, no empirical study based on the source code of the backdoor attacks has been conducted so far. In this paper, we conduct an empirical study to understand how backdoor attacks on Ethereum smart contracts are performed in the real world by analyzing all smart contracts with source code. To this end, we also propose a new investigation tool for the empirical study, named BACCA. We then identify several key insights. First, we totally found 288,440 contracts for backdoors attacked, called contract backdoors, including potential ones. The most significant backdoor attack is DisableTransfer, which disables transfers of assets to other addresses, and we identify 211,687 smart contracts affected by this attack. Second, several backdoor attacks are combined with other types of backdoor attacks, called combination contract backdoors, and 90.9% of DisableTransfer are combination contract backdoors. Third, GenerateToken, which enables an adversary to generate new cryptoassets, is the largest as a backdoor without any combinations, i.e., unique contract backdoors, and 23.8% of GenerateToken are the unique contract backdoors. Fourth, when we analyze the number of transactions sent to the above contract backdoors to identify their gas consumption in the real world, we identify that about 9 trillion dollars have been consumed by them. We also found a remarkable contract backdoor that receives more than a million transactions, resulting in gas consumption of about two billion dollars. We further discuss implications for the design of analysis tools for subsequent work and the impact of compiler updates on the above backdoor attacks.
В статье рассматриваются принципы диверсификации портфеля казначейств децентрализованных автономных организаций (DAO), функционирующих на основе собственных криптоактивов. В условиях высокой волатильности и нестабильности криптовалютных рынков управление казначейским портфелем приобретает ключевое значение для обеспечения финансовой устойчивости DAO. В работе используется метод сценарного анализа, основанный на положениях классической портфельной теории Марковица (mean-variance), с целью оценки влияния структуры портфеля на чувствительность стоимости казны к рыночным шокам. Показано, что включение низковолатильных активов, в частности стейблкоинов и нативных монет блокчейнов первого уровня, позволяет существенно снизить совокупный риск портфеля при сохранении экспозиции к росту индустрии Web3. На основе анализа практик управления казначействами ведущих DAO сформулированы рекомендации по оптимальной диверсификации активов при наличии собственного токена DAO для смягчения просадки стоимости казны при неблагоприятных рыночных сценариях. This paper explores the principles of portfolio diversification for the treasuries of decentralised autonomous organisations (DAOs) managing their own crypto-assets. In environments characterised by high volatility and structural instability within cryptocurrency markets, effective treasury portfolio management becomes essential for maintaining the financial sustainability of DAOs. The study utilises a scenario-based analysis rooted in the classical mean-variance portfolio theory introduced by Markowitz to evaluate how portfolio structure influences the sensitivity of treasury value to market shocks. The findings show that including low-volatility assets, especially stablecoins and native layer 1 blockchain assets, markedly reduces overall portfolio risk while still allowing exposure to the growth of the Web3 sector. Drawing on an analysis of treasury management practices among leading DAOs, the paper offers recommendations for optimal asset diversification in the context of a native DAO token to minimise overall treasury risk.
Muhammad Izzuddin Al Ayzami, Achmad Fathoni, Moh. Sirojuddin
Penelitian ini mengkaji apakah aset digital memenuhi unsur māl mutaqawwam dan dapat menjadi mahar yang sah menurut fikih Islam. Proliferasi aset digital meliputi cryptocurrency, stablecoin, non-fungible token (NFT), utility token, dan security token telah menghadirkan pertanyaan baru yang belum terpetakan dalam hukum keluarga Islam (Ahwal Syakhshiyyah), khususnya tentang kelayakan aset digital sebagai mahar perkawinan. Kajian-kajian sebelumnya dominan membahas kehalalan cryptocurrency secara umum tanpa melakukan evaluasi sistematis terhadap berbagai kategori aset digital berdasarkan syarat-syarat mahar yang ditentukan fikih klasik. Penelitian ini menggunakan metode library research dengan pendekatan normatif-konseptual, merujuk pada sumber-sumber fikih primer empat mazhab Sunni (Hanafi, Maliki, Syafi'i, dan Hanbali) serta lembaga fatwa kontemporer yang otoritatif, meliputi DSN-MUI, AAOIFI, dan Majma' al-Fiqh al-Islami. Kajian ini mengintegrasikan enam kerangka teoritis māl, māl mutaqawwam, milkiyyah, qabd, gharar, dan syarat-syarat mahar dan menerapkannya secara analitis terhadap setiap kategori aset digital. Temuan penelitian ini menunjukkan bahwa tidak semua aset digital memiliki status hukum yang identik. Stablecoin dan utility token yang dilindungi hukum umumnya memenuhi syarat māl mutaqawwam dan dapat berfungsi sebagai mahar yang sah apabila mekanisme qabd yang jelas ditetapkan. Cryptocurrency yang sangat volatil menimbulkan kekhawatiran signifikan terkait gharar dan defisiensi taqawwum, sehingga statusnya bergantung pada pengakuan regulasi dan stabilitas pasar. NFT dapat menjadi mahar yang sah sepanjang aset yang mendasarinya memberikan hak ekonomi yang diakui dan dapat dialihkan. Security token memiliki klaim terkuat sebagai mahar mengingat sifatnya yang didukung aset dan pengawasan regulasi. Penelitian ini memberikan kontribusi berupa matriks klasifikasi hukum komprehensif untuk aset digital sebagai mahar dan mengusulkan kerangka konseptual untuk integrasi aset digital ke dalam hukum keluarga Islam kontemporer.
The Adaptive Neural Gossip Protocol (ANGP) is a fully decentralized, asynchronous consensus mechanism designed for Directed Acyclic Graph (DAG) based distributed ledgers. Unlike classical Byzantine Fault Tolerant (BFT) systems that rely on leader election or quorums, ANGP uses:• Amedian-based consensus computed from predictions exchanged via gossip.• A continuous reputation engine that distinguishes honest nodes from Byzantine attackers, including coordinated collusion, rare attacks, sensor faults, and network impairments.• Alightweight Proof-of-Work (PoW) layer (SHA-512/256) to prevent Sybil identity floods, while keeping the core protocol free of staking or token-based governance.ANGP tolerates up to 44% coordinated attackers and 66% uncoordinated attackers with no degradation in honest node safety. It operates asynchronously, requires no global time synchronization, and self-heals under packet loss and network delays. This document provides the complete architectural blueprint, component specifications, security analysis, and integration guidelines for building a production-grade DAG based cryptocurrency or distributed application on top of ANGP.
Cryptocurrency price prediction is a significant challenge in quantitative investment. In recent years, time series models have made significant progress in financial forecasting tasks, especially in the stock market. Despite the growing performance over the past few years, we question the validity of this line of research in cryptocurrency prediction. Specifically, time series models (e.g., LSTM, GRU, and Transformers) are effective at extracting temporal relationships in stock market data. However, in pure price-based cryptocurrency prediction, facing data with extreme volatility and wild swings, time series models have difficulty learning effective information. To validate our claim, we propose CryptoGAT, a lightweight Graph Attention Network that recasts cryptocurrency pure price prediction as a cross-asset graph problem rather than a temporal modeling task. Extensive experiments on real cryptocurrency benchmarks demonstrate that our proposed CryptoGAT outperforms various state-of-the-art forecasting methods with a notable margin. Moreover, we conduct comprehensive empirical studies to explore the fundamental differences exposed by time series models in stock and cryptocurrency prediction: differences in predictability of the signal and cross-asset dependencies. This finding opens up new research directions for the cryptocurrency pure price prediction task and inspires further graph-based exploration in the field. The source code is available at https://github.com/FanBroWell/CryptoGAT
Blockchain technology has evolved from its origins as the foundational ledger for cryptocurrencies to a disruptive paradigm for decentralized, transparent, and secure data management across numerous sectors. This review paper provides a systematic analysis of core blockchain architectures, consensus protocols, and smart contract functionalities that enable its diverse applications. We examine the transition from public, permissionless networks to private and consortium models tailored for enterprise needs. The paper surveys seminal and contemporary research across key domains including decentralized finance (DeFi), supply chain provenance, healthcare data exchange, electronic voting, and the Internet of Things (IoT). By synthesizing findings from foundational protocols to cutting-edge cross-chain solutions, we identify common technical motifs and domain-specific implementations. Furthermore, the review delineates persistent challenges such as scalability trilemmas, interoperability gaps, regulatory uncertainty, and significant energy consumption. This consolidated analysis aims to serve as a reference for researchers and practitioners, highlighting both the transformative potential and the critical limitations of blockchain techniques as a trustless infrastructure for the digital age.