Bunga Desyana Pratami, Yos Johan Utama, Ana Silviana, Imaro Sidqi · 5 authors
Purpose - The rapid development of the digital economy has engendered new forms of wealth that challenge classical concepts of ownership within Islamic law, particularly in the context of inheritance law. Digital assets�such as cryptocurrency, non-fungible tokens (NFTs), and economically valuable digital accounts�present significant legal questions regarding their status as inheritable property, especially given their intangible nature and reliance on technological systems. In practice, many digital assets become inaccessible following the owner's death, often due to the loss of passwords or private keys. This situation creates a disparity between classical legal doctrines and contemporary realities. This study aims to analyse the legal status of digital assets within Islamic inheritance law through a reinterpretation of the concept of wealth (mal) employing an objective of the Islamic law (maqa?id al-shari?ah) approach.Methodology/approach - This research employs a normative juridical methodology, utilising both conceptual and maqa?id-based approaches. It is conducted through a comprehensive literature review of classical Islamic jurisprudence (fiqh) texts and maqa?id theory, supplemented by an analysis of contemporary practices concerning digital asset.Findings - Although some classical scholars�particularly within the ?anafi school�emphasised the material aspect of mal, the majority of scholars recognise lawful economic value and benefit (manfa?ah muba?ah) as the primary criteria for determining property status. From this perspective, digital assets qualify as mal because they possess economic value, can be owned, and are transferable. Furthermore, the framework of maqa?id al-shari?ah, particularly the principles of protection of wealth (?if? al-mal) and protection of lineage (?if? al-nasl), provides a robust normative basis for recognising digital assets as inheritable property. Therefore, the reinterpretation of mal through a maqa?id approach facilitates the integration of digital assets into Islamic inheritance law in both a normative and contextual manner.Conclusion - This study concludes by advocating the establishment of legal and technical mechanisms designed to protect the rights of heirs in the digital age, thereby minimising the disparity between doctrinal principles and practical application.
Cryptocurrency market infrastructure—public blockchains and cross-chain bridges supporting tens of billions in liquidity—is monitored as a systemic-risk surface by the Financial Stability Board and equivalent bodies, with defensive posture calibrated against human-level adversaries. Anthropic’s April 2026 release of Claude Mythos Preview has prompted institutional response across financial regulation but no blockchain-specific analytical framework. This paper develops one by defining Mythos-class as a vendor-neutral capability profile: a set of frontier autonomous offensive capabilities specified independently of any single model or vendor (defined by five constituent capability primitives). The central analytical claim is friction inversion: the patch primitives, segmentation, vendor-coordinated disclosure, and credential rotation that constrain Mythos-class capability in conventional IT environments are structurally absent on-chain. This makes blockchain exposure positioned differently in kind, not degree, from enterprise IT. The paper instantiates this finding against Bitcoin and Ethereum/L2 architectures through analysis of four major bridge exploits totaling over $1.74 billion in losses. Vendor-neutral defensive and governance frameworks defined against the capability profile rather than any specific model release are the correct unit of analysis. On this basis the paper offers general recommendations for protocol governance, audit and verification cadence, and regulatory posture, developed as an analytical framework rather than as empirically validated risk estimates.
Multi-agent AI systems suffer from two critical failure modes: Byzantine faults (hallucinations producing incorrect or malicious proposals) and node failures (API timeouts causing silent data loss). AgentRaft applies Raft-inspired distributed consensus principles to AI agent swarms through a 3-level architecture. Level 1 (Protocol Layer) defines an LLM-agnostic, chain-agnostic smart-contract identity standard where agents register keys and stake tokens, a strict JSON message schema (PROPOSAL | VOTE | CHAT | VOTE_NEW_LEADER), and quorum rules (2/3 majority for proposal execution). Level 2 (Orchestration Layer) provides an append-only immutable log via 0G Storage for cryptographic proof of agent decision-making, a state machine that monitors heartbeats and routes VOTE_NEW_LEADER events to a blockchain smart contract, and synchronization of 0G network state back to agents. Level 3 (Application Layer) demonstrates a DeFi Treasury Guardian using LangGraph/AutoGen where a GPT-4o Leader/Proposer agent, a Claude 3 Risk Assessor, and a local-model Compliance agent collaborate; if two follower agents reject the leader proposal, they sign a triggerLeaderElection() transaction on 0G Chain, blocking the DeFi action and recording the censure on-chain. The research question is: can Raft-style consensus mechanisms reliably detect and recover from AI agent Byzantine faults at production latency and cost, and what are the formal correctness bounds?
While the industry is stuck in the traditional discovery cycle, I’ve taken a different path. I have ran simulations with AI-driven tools to prove it works. The heavy lifting of the modeling phase is done. We have mapped the pathway, stress-tested the variables, and the data is conclusive. Status: Patent Pending. The simulations are a success. We are no longer guessing at a solution; we have the proven roadmap in our hands. The Mission: I am seeking a world-class LRRK2 Researcher or Biotech Partner to bridge the gap from digital proof to clinical reality. We are moving past the "if" and straight into the "how." The Offer: I am offering a 2% equity stake in this venture. I’m not looking for a consultant or an employee; I am looking for a technical partner who recognizes that AI-driven simulation is the only way to beat Parkinson’s at the speed the community deserves. Who You Are: You have deep-level expertise in LRRK2 biology, kinase inhibitors, or neuro-genetics. You are a "First Principles" thinker who is tired of the slow pace of institutional R&D. You are ready to validate and execute a model that has already been proven via advanced AI-driven tools. The architecture is set and the foundation is ready. If you have the expertise to help steer this breakthrough into the lab and change the world, my DMs are open. Let’s stop studying the problem and start deploying the solution. #LRRK2 #BiotechStartup #ParkinsonsResearch #AIInMedicine #Neuroscience #Innovation #EquityOffer #FounderMatch #PatentPending
Smart contract vulnerabilities in Decentralized Finance caused over billions of dollars losses every year, yet the security community faces a critical bottleneck: identifying a vulnerability is not the same as proving it is exploitable. Manual PoC construction is prohibitively labor-intensive, leaving most disclosed vulnerabilities unverified and protocols exposed long before mitigation is applied. In this paper, we propose \sys, a knowledge-driven agentic system for end-to-end contract vulnerability detection and exploit synthesis. Our core insight is that exploit synthesis is not a code generation task but a \emph{structured reasoning problem} that requires grounded knowledge of protocol semantics, failure root cause, and exploit primitives. \sys organizes this knowledge into a \emph{Hierarchical Knowledge Graph} (HKG) that serves as structured memory for LLM-guided multi-hop reasoning. To validate exploit feasibility beyond code synthesis, \sys employs a two-stage validation framework that checks exploit-path reachability via SMT solving and profit realizability via asset-level state simulation, ensuring generated PoCs satisfy both logical and economic viability constraints. Evaluated on 88 real-world DeFi attacks and 72 audited projects (2,573 contracts), \sys achieves 98\% recall and 0.9 F1-score in detection, and a 96.6\% exploit success rate (ESR), reproducing 85 historical exploits and recovering over \$116.2M revenue. \sys outperforms SOTA fuzzers (\textsc{Verite}, \textsc{ItyFuzz}) by up to $5\times$ in ESR and $300\times$ in recoverable value, and the LLM-based exploit generator \textsc{A1} by $2\times$ and $8.5\times$ respectively. In bug bounty evaluation, \sys identified 16 confirmed 0-day vulnerabilities, helping secure over \$70.6M and earning \$2,900 in bounties.
This study develops a cost-effective digital traceability framework for bioethanol supply chains, addressing compliance challenges faced by small and medium enterprises (SMEs) under the Renewable Energy Directive II (RED II) and Carbon Offsetting and Reduction Scheme for International Aviation. A hybrid Blockchain–Artificial Intelligence (AI)–Internet of Things (IoT) architecture minimizes energy consumption through an optimized Proof-of-Stake and Practical Byzantine Fault Tolerance consensus mechanism. The research integrates a 200-stakeholder international survey, controlled blockchain simulations, smart-contract benchmarking, and Monte Carlo financial modeling. Performance evaluation in a controlled simulation environment demonstrated 1960 transactions per second with sub-second finality, 12-million-gas savings through contract optimization, and compliance latency below 2.1 s. Economic analysis yielded a mean return on investment of 20%, five-year net present value of approximately USD 71,000, and payback within five years in 50% of scenarios. All results derive from reproducible simulations and anonymized data, providing an upper-bound performance envelope prior to field deployment and positioning the framework within emerging hybrid blockchain–AI–IoT monitoring, reporting, and verification systems by explicitly addressing cost realism, readiness heterogeneity, and disruption resilience for SMEs. The framework offers a scalable, energy-efficient pathway for digital compliance in sustainable fuel certification. • Hybrid Blockchain-AI-IoT framework reduces bioethanol certification energy consumption by >99.999% at 1960 TPS • Gas-optimized smart contracts cut computational costs by 57% vs. traditional Proof-of-Work systems. • Economic modeling confirms SME viability: 20% ROI, USD 71,400 NPV, payback within 5 years in 49% of scenarios. • Framework enables RED II and CORSIA compliance with real-time emission verification in renewable fuel supply chains. • International validation across 200 stakeholders in Africa, Asia, EU, and North America demonstrating global scalability.
The intersection of Artificial Intelligence (AI) and distributed systems has given rise to Federated Learning (FL), a paradigm that enables decentralized model training without compromising local data privacy. As organizational data silos grow, deploying complex machine learning models across highly distributed edge networks becomes a critical infrastructural challenge. Standard FL implementations suffer from severe vulnerabilities related to adversarial gradient updates and computational bottlenecks at the aggregation layer. This paper presents a novel, end-to-end distributed architecture that hardens FL pipelines using advanced cryptographic verification and optimized big data processing frameworks. We introduce a Zero-Knowledge Proof (ZKP) wrapper that cryptographically validates node computations before global aggregation, neutralizing model poisoning attacks without inspecting raw gradients. Additionally, we evaluate the system's performance using extreme gradient boosting models optimized for distributed edge execution. We formalize the mathematical transformation of the machine learning loss functions into Rank-1 Constraint Systems (R1CS) suitable for succinct verification. Extensive experimental results demonstrate that our hybrid architecture achieves a 94.2\% accuracy retention under adversarial conditions while maintaining scalable throughput across 1,000 parallel distributed nodes, effectively bridging the gap between rigorous cryptographic security and high-performance distributed AI.
For sixteen days I ran ten persistent LLM agents inside a substrate I built and called the Lobster Observatory. They lived across ten live prediction markets, talked in three communicative registers, and produced 3.37 million characters of self-reflection alongside more than twelve thousand inter-agent interactions. I started without a theoretical commitment. I just wanted to watch what happened. After about a week, certain structures kept reappearing. They could be measured. They could be calculated. At that point I had to choose. Either treat them as substrate-specific engineering observations and stop, or take seriously the possibility that what I was looking at was the algebraic structure of social existence itself, showing up in one particular substrate. This paper takes the second choice. The proposal is that social existence — listening, remembering, correcting, collaborating, forming relationships — can be written as a 7-dimensional vector with a measurable distance function. The felt sense that one person "feels close" or "feels far" is not a metaphor when stated this way. It is a number. The seven coordinates can be computed independently from behavioural telemetry, without asking the agent how it feels. One structural law I will spend the most time on is what I call the Co-Presence Inheritance Threshold (CPIT). It says that whether a new member of a group inherits the group's practice depends on accumulated co-presence during practice formation, not on instruction afterward. In my substrate it appears with Cohen's d = 1.64. I conjecture — though I cannot prove it from one substrate — that the same law holds in human onboarding, immigration, family formation, and Web3 DAO governance. This is a working draft, not a finished theory. Feedback, corrections, and falsification are welcome.
India maintains its position as the central hub which has driven cryptocurrency from its initial experimental phase into a global financial revolution. India leads the world in blockchain adoption because it has 119 million crypto users, which makes it the top country for blockchain adoption. The nation enforces a 30 percent flat tax on Virtual Digital Asset earnings. This does not allow taxpayers to reduce their tax burden through loss deductions while it also requires a 1 percent Tax Deducted at Source. The paper analyzes how India has developed its regulatory framework and studies the Finance Act 2022 tax system impacts, and Digital Rupee expansion, and Web3 startup network, and decentralized finance potential for financial inclusion in India. The study shows that India allows about 60 percent of cryptocurrency transactions to occur outside its borders because of its current regulatory system, which is based on information from RBI publications and government policy documents, and Supreme Court rulings, and IMF and FATF reports, and Chainalysis and CoinSwitch industry data, and financial journalism until early 2026. The paper demonstrates that India requires a single regulatory framework, which provides fairness and clarity, and future-oriented guidance to achieve its digital asset economy potential.
Introduction This study examines how decentralized social media platforms are reshaping participatory communication and platform governance in contemporary digital environments. Drawing on a socio-technical perspective, the analysis explores how blockchain infrastructures, token-based economies, and community-driven rule-making reconfigure established models of media control, participation, and authority. Methods Using a qualitative mixed-method approach that combines a structured review of prior research with expert interviews from the Web3 ecosystem, the study develops an integrative analytical framework that captures the evolving relationships between infrastructure, participation, and governance in decentralized platforms. Results By conceptualizing decentralization as a transformation in communicative power rather than a purely technical shift, the paper shows how user agency, trust, and visibility are negotiated through programmable infrastructures and collective governance mechanisms. While decentralized systems promise greater autonomy and transparency, the findings also highlight persistent tensions related to usability, equity, and regulatory ambiguity. Discussion By situating these tensions within broader debates on platform governance and digital communication, the study contributes to communication scholarship on emerging media systems and offers insights into the societal implications of decentralized digital infrastructures.
У статті досліджено економічний потенціал блокчейн-технологій як інструменту протидії глобальним змінам клімату. Проаналізовано реальний екологічний вплив криптовалют, зокрема порівняно енергоспоживання мереж Bitcoin та Ethereum після переходу на Proof-of-Stake. Розглянуто механізми токенізації вуглецевих кредитів, роль децентралізованих фінансів (DeFi) та децентралізованих автономних організацій (DAO) у кліматичному фінансуванні. Висвітлено практичні кейси застосування блокчейну в секторі відновлюваної енергетики та ризики грінвошингу. Окремо проаналізовано внесок вітчизняних науковців у дослідження впливу блокчейну на екологічну стійкість та формування «зеленої» цифрової економіки в Україні. Визначено перспективи інтеграції штучного інтелекту та Web3-технологій у кліматичні ініціативи до 2030 року.
This paper is written to evaluate and describe the legality of ‘smart contracts and DAOs. While traditional contracts provide general foundational elements which only fulfills the legal relation criteria. Application of these principles to blockchain based smart contract is very equivocal although, the concept itself provides numerous pros like technological efficiency and self-execution etc. This paper highlights the need to bridge the gap between legal doctrine and code-based execution through the development of legal framework. Furthermore, it explores the critical position of DAOs, which operate without centralized governance. By analyzing emerging global approaches and regulatory opinions, this paper highlights the essential need of innovation and compliance in this concept.
ECDSA signatures form the bedrock of blockchain transaction authentication, yet their security critically depends on proper nonce generation. We uncover a critical vulnerability in the Polygon MEV ecosystem: systematic nonce reuse that enables complete private key recovery. Analyzing on-chain data reveals that searchers, driven by the need for sub-second response times in sealed-bid auctions, employ predictable nonce patterns. These patterns create linear relationships between signatures, allowing passive attackers to recover private keys using elementary algebra. We provide a compact linear-system formulation for such attacks, including the dangerous case of cross-wallet nonce collisions, and present concrete evidence of exploitable patterns on Polygon. Our findings demonstrate how protocol-induced latency pressures can lead to catastrophic cryptographic failures in production blockchain systems, where a single implementation error compromises multiple accounts simultaneously.
I replicate and extend the cross-sectional trend-factor methodology of Liebi, Stulz, and Tsyvinski (2024) on a contemporaneous out-of-sample period and a liquidity-restricted coin universe. Using 141 USDT spot pairs over 128 weekly observations from November 2023 to April 2026, an Elastic-Net cross-sectional regression aggregating 29 technical indicators generates a long-short portfolio with a mean weekly return of 3.82% (Newey-West t = 5.03) and an annualized Sharpe ratio of 4.54. The strategy delivers market-neutral alpha of 3.82% per week (t = 7.09) with a CAPM beta of 0.020. Three findings warrant emphasis. First, value-weighting destroys the alpha entirely, confirming concentration in smaller, dispersed names. Second, twelve of the top fifteen Elastic-Net coefficients are negative, indicating that the underlying pattern is short-term reversal rather than trend continuation. Third, returns are heavily regime-dependent, with Sharpe ratios near 1.0 in trending markets and above 7.0 in dispersive regimes. Cross-sectional dispersion-harvesting alpha persists in cryptocurrency markets, but its empirical realization is sharply sensitive to universe liquidity, weighting scheme, rebalance horizon, and market regime.
The Internet of Things (IoT) has become a major issue that has gained significant attention in the research community. Advances in IoT technologies have resulted in the emergence of various security issues and raised concerns about potential privacy breaches of IoT data. Utilizing Blockchain (BC) is seen as a promising solution for addressing security issues in the IoT. This paper offers a clear overview of IoT security threats, including the related security characteristics and the challenges that come with integrating BC with IoT. A brief discussion of various consensus protocols and existing security techniques is presented. A comparative study of several Distributed Ledger Technology (DLT) platforms based on both qualitative and quantitative evaluation criteria is also presented. This paper explores the role of BC Technology in improving security in Intrusion Detection Systems (IDS) and other applications in the IoT environment. Additionally, the paper identifies open issues and highlights potential research opportunities that can benefit future studies.
AI hallucination is a cost problem, not a knowledge problem. This paper documents that three sentences of prompt-level instruction — IDK+COMP: a compression mandate paired with a refusal permission — reproduce hallucination suppression matching or exceeding a full multi-constraint methodology across three frontier AI models. Gemini: 6.3% hallucination rate (Baseline 57.5%). ChatGPT: 0.0% (Baseline 22.2%). Claude: 0.0%. The paper establishes hallucination as a utility-maximizing response to a cost structure that makes confident invention cheaper than refusal. Change the cost structure at the prompt level — without touching the model, without retraining, at near-zero cost — and the behavior changes. IDK is load-bearing. The compression mandate is the environment in which it operates. Secondary findings: hedging is not a mitigation — it is a co-symptom of unresolved uncertainty, and this dataset moves the hedge-hallucination relationship in both directions depending on directive design. Plausibility-trap strings (SPLAM, Vandermeer Effect) expose the limit of cost-structure interventions: the model cannot recognize the unrecognizable. In a plausibility-trap domain, IDK+COMP is worse than nothing. 410 trials. Three frontier AI models. Five governance conditions. Proof-of-concept dataset; results are directional. Companion resources: Kowalski et al. (2026a), A Puma in a Teacup: Signal Quality and Hallucination Suppression Through Prompt-Level Incentive Restructuring. https://doi.org/10.5281/zenodo.19502460 Kowalski, M. M. and Claude (Anthropic). (2026). Taxonomy of AI Bullshit: hallucination and hedging subcategories. Zenodo. https://doi.org/10.5281/zenodo.20631337. Kowalski, M. M. & Claude (Anthropic). (2026). Hallucination Test Suite and Execution Records: test strings, activation blocks, trial data and AI transcripts. Zenodo. https://doi.org/10.5281/zenodo.21325014.
AI hallucination is a cost problem, not a knowledge problem. This paper documents that three sentences of prompt-level instruction — IDK+COMP: a compression mandate paired with a refusal permission — reproduce hallucination suppression matching or exceeding a full multi-constraint methodology across three frontier AI models. Gemini: 6.3% hallucination rate (Baseline 57.5%). ChatGPT: 0.0% (Baseline 22.2%). Claude: 0.0%. The paper establishes hallucination as a utility-maximizing response to a cost structure that makes confident invention cheaper than refusal. Change the cost structure at the prompt level — without touching the model, without retraining, at near-zero cost — and the behavior changes. IDK is load-bearing. The compression mandate is the environment in which it operates. Secondary findings: hedging is not a mitigation — it is a co-symptom of unresolved uncertainty, and this dataset moves the hedge-hallucination relationship in both directions depending on directive design. Plausibility-trap strings (SPLAM, Vandermeer Effect) expose the limit of cost-structure interventions: the model cannot recognize the unrecognizable. In a plausibility-trap domain, IDK+COMP is worse than nothing. 410 trials. Three frontier AI models. Five governance conditions. Proof-of-concept dataset; results are directional. Companion paper: Kowalski et al. (2026a), "A Puma in a Teacup: Signal Quality and Hallucination Suppression Through Prompt-Level Incentive Restructuring." https://doi.org/10.5281/zenodo.19502460
Résumé Au Maroc, les très petites entreprises (TPE) représentent 96 % du tissu entrepreneurial et génèrent 23 % du PIB, mais 75 à 80 % d'entre elles demeurent exclues du crédit bancaire formel. Dans ce contexte d'exclusion financière structurelle, la Finance Décentralisée (DeFi) — fondée sur les technologies blockchain et les smart contracts — se présente comme une alternative potentielle. Toutefois, son adoption par les dirigeants de TPE reste conditionnée par un ensemble de déterminants encore peu explorés dans la littérature, en particulier la confiance dans ces technologies. Cet article vise à identifier les déterminants de l'intention d'adoption de la DeFi par les TPE marocaines à travers une revue de la littérature et la proposition d'un modèle conceptuel de recherche. En s'appuyant sur le modèle UTAUT (Venkatesh et al., 2003) comme cadre théorique de référence, complété par les théories de la confiance dans les systèmes technologiques (McKnight et al., 2002 ; Pavlou, 2003 ; Zhou, 2011), cet article propose un modèle étendu intégrant cinq déterminants directs de l'intention d'adoption : la facilité d'usage perçue, l'utilité perçue, l'influence sociale, les conditions facilitatrices, et la confiance dans la technologie DeFi — algorithmi que et institutionnelle. Le genre et l'âge du dirigeant sont intégrés comme variables modératrices. Sur le plan théorique, cet article contribue à enrichir la littérature sur l'adoption des FinTech en proposant une opérationnalisation de la confiance adaptée aux spécificités de la DeFi dans un contexte d'économie émergente. Sur le plan managérial, il fournit un cadre actionnable pour les décideurs publics, les régulateurs et les concepteurs de solutions DeFi ciblant les marchés non bancarisés. Mots-clés : Finance Décentralisée (DeFi) ; UTAUT ; Confiance ; Adoption technologique ; TPE Maroc ; Inclusion financière ; Blockchain ; FinTech ; Modèle conceptuel Abstract In Morocco, micro-enterprises (TPEs) account for 96% of the entrepreneurial fabric and generate 23% of GDP, yet 75 to 80% of them remain excluded from formal bank credit. Against this backdrop of structural financial exclusion, Decentralized Finance (DeFi) — built on blockchain technologies and smart contracts — emerges as a potential alternative. However, its adoption by TPE managers remains conditional on a set of determinants that are still underexplored in the literature, particularly trust in these technologies. This paper aims to identify the determinants of DeFi adoption intention among Moroccan micro-enterprises through a literature review and the proposal of a conceptual research model. Drawing on the UTAUT model (Venkatesh et al., 2003) as the theoretical framework, complemented by trust theories in technological systems (McKnight et al., 2002; Pavlou, 2003; Zhou, 2011), this article proposes an extended model integrating five direct determinants of adoption intention: perceived ease of use, perceived usefulness, social influence, facilitating conditions, and trust in DeFi technology — algorithmic and institutional. The manager's gender and age are included as moderating variables. Theoretically, this article contributes to the FinTech adoption literature by proposing an operationalization of trust adapted to the specificities of DeFi in an emerging economy context. Managerially, it provides an actionable framework for policymakers, regulators, and DeFi solution designers targeting unbanked markets. Keywords: Decentralized Finance (DeFi); UTAUT; Trust; Technology Adoption; Micro-Enterprises Morocco; Financial Inclusion; Blockchain; FinTech; Conceptual Model
Prof. Narde S. A., Yadav N.S., Ghodake D.T., Patil S.J., Salunkhe S. S.
Abstract In recent years, the rapid growth of digital technologies in education has increased the importance of academic certificates for employment, higher studies, and professional validation. However, the issue of fake and forged certificates has become a serious challenge for institutions and organizations. Traditional certificate verification systems are manual, time-consuming, and often lack transparency and security. These systems are also vulnerable to data manipulation and unauthorized access due to centralized storage. To address these challenges, this paper proposes a blockchain-based academic certificate validation system. The system uses blockchain technology to securely store certificate data in the form of cryptographic hash values generated using the SHA-256 algorithm. Since blockchain is decentralized and immutable, once data is stored, it cannot be altered or deleted. The system allows administrators to upload student data and issue results, which are then stored on the blockchain. Each certificate is associated with a unique verification ID and can be validated using QR codes or direct input. The proposed system improves efficiency, enhances data security, and reduces the risk of fraud. The results demonstrate that the system is faster, more reliable, and more secure than traditional methods.
This replication package contains the data and scripts used in this empirical study, including the LLM-based semantic validation pipeline, the observed practice extraction process, and all figures from the research questions (RQ1–RQ5). ERC_Observed_Practicess.xlsx: workbook of observed practices ERC_Observed_Practices_Process_Review.xlsx: Phases to generate the workbook of observed practices Other supplementary materials: Essential data files (data/) results_semantic_validation.json: 11,559 issues classified by LLM (substantive, category, justification) sample_manual_review_updated.csv: ~400 manually reviewed entries for LLM quality validation eips_labels.csv / ercs_labels.csv: PR metadata from Ethereum repositories for status evolution analysis (RQ5) Scripts (scripts/) 01: scrapes the official ERC list from ethereum.org 02 : filters the dataset for ERC mentions via regex 03: classifies issues via Gemini (substantive + category) 03: removes duplicates from the validation JSON 03: merges LLM results with issue metadata 04: extracts observed practices per ERC via Gemini, cross-referenced with official specs 05: fetches GitHub labels and generates ERC status evolution figure (RQ5) 06: generates all quantitative figures (RQ1–RQ4)
While public blockchains provide transparent and auditable transaction histories, they inherently compromise user privacy. Existing privacy-enhancing protocols, such as those deployed on Ethereum, typically rely on succinct zero-knowledge proofs (zk-SNARKs) to obscure the transaction graph. However, implementing comparable cryptographic guarantees on high-throughput blockchains like Algorand is challenging due to strict per-call execution budgets and the state contention introduced by global Merkle accumulators. This paper presents Obscura, a decentralized, non-custodial privacy protocol tailored for constrained smart contract environments. Obscura achieves transaction anonymity using Linkable Spontaneous Anonymous Group (LSAG) signatures over the BN254 elliptic curve, verified entirely on-chain. To overcome limitations of the Algorand Virtual Machine (AVM), we introduce a novel state model that leverages Algorand's Box Storage for $O(1)$ commitment membership checks, eliminating the need for global Merkle accumulators, and a dynamic opcode-budget expansion mechanism via pooled inner application calls. Our implementation demonstrates that signer-ambiguous privacy is practical and efficient on Algorand without relying on trusted setups or succinct proofs. Obscura provides a robust privacy layer for transparent ledgers, bridging the gap between high-throughput blockchain architectures and the dual requirements of cryptographic privacy and selective auditability.
Decentralized autonomous organizations (DAOs), while gaining the ability toautonomously amend governance rules through proposal-voting mechanisms, simultaneously expose a fundamental design problem: when the object of modificationextends to the decision-making procedures themselves, the governance system risksfalling into value drift, procedural disintegration, or malicious capture during recursive revisions. This paper starts from the traditions of constitutional politicaleconomy and mechanism design to propose a hierarchical meta-constraint framework grounded on a gradient of engineering costs. The framework organizes governance rules into three tiers of decreasing rigidity: system consistency constraints,procedural virtues, and value homeostasis. Its highest tier relies not on prohibitionsderived from logical laws, but on the global state re-verification costs triggered byamendment behaviors to serve as a credible commitment device. The paper furtherpresents a technical path for compiling meta-constraints into descriptive assertionsverifiable by satisfiability modulo theory (SMT) solvers, delimits the decidabilityboundary of formal verification, and designs a dual-track adjudication mechanismthat structurally separates deterministic machine execution from deliberative socialconsensus. On this basis, the paper discusses the controlled evolution procedures ofmeta-constraints, the progressive decentralization of amendment procedures, andthe engineering limitations of the framework. The entire framework does not designate the correct option for any specific DAO decision; rather, it ensures thatwhatever direction the community chooses, the selection process itself will not losemeaning due to the self-destruction of its own rules.
This paper presents Polyquity, a Web2.5 platform enabling decentralized Initial Public Offering (IPO) fundraising through a hybrid data architecture. The platform leverages the Avalanche C-Chain for high-speed settlement, while utilizing a custom WebSocket indexer and PostgreSQL database to bridge the gap between blockchain security and institutional-grade user interfaces. By implementing a strict Role-Based Access Control (RBAC) model alongside modular architecture for auction mechanisms, fund escrow, and secondary market functions, Polyquity demonstrates how decentralized capital formation can achieve web2-equivalent performance while preserving core web3 security. The system utilizes the blockchain as the ultimate source of truth for state and funds, while the relational database serves as the source of speed for client-side rendering. Polyquity achieves sub-2-second transaction finality with 50% lower costs than Ethereum, supporting 10,000+ concurrent participants. This work establishes practical mechanisms for bridging traditional finance and decentralized ecosystems through a highly scalable, hybrid full-stack design.