Learn more about Theta Network and its impact on the development of decentralized infrastructure via blockchain-enabled media distribution, edge computing, AI integration, and Web3 innovation. With this in-depth overview, you will gain valuable information about its technology, features, practical applications, and future perspectives, emphasizing the need for thorough research before making an investment decision. If you are interested in blockchain, then this article is for you!
Many administrative processes, such as internship agreement processes, often rely on manual approval workflows and centralized record-keeping. This makes the process susceptible to delays and unauthorized modification while introducing limited traceability. This study presents StajChain, a permissioned blockchain-based multi-party internship management system developed using Hyperledger Fabric. The proposed system implements the complete internship agreement lifecycle through smart contracts and enforces role-based authorization using Hyperledger Fabric CA. The architecture consists of a React frontend, a NodeJS backend, an off-chain SQLite database, and the on-chain Fabric ledger. Users such as students, companies, faculty internship committee members, and the central internship unit can perform specified operations according to their role and identity. The agreement lifecycle follows predefined sequential steps, and at each step, the ledger status is updated and recorded securely. Furthermore, the system was evaluated using functional and performance tests, indicating acceptable throughput and latency for verifiable administrative workflows. This implementation demonstrates how permissioned blockchain technology can improve transparency, integrity, and accountability while preserving controlled access to institutional data and providing a working prototype that can be used in various future systems.
x402 is an emerging payment protocol for Web APIs and autonomous AI agents. x402 extends HTTP 402 with a payment negotiation flow and delegates payment proof verification and on-chain settlement to third-party facilitators. As a result, facilitators serve as a shared payment infrastructure for many independent merchants. This centralizes trust and validation in one component, so a single flaw can affect many services. Despite rapid adoption by major vendors and economically meaningful mainnet activity, the security posture of real-world x402 deployments remains poorly characterized. We present the first systematic study of authorization correctness and execution safety in current facilitator-mediated x402 deployments in the wild, identifying eight security rules for facilitators as critical payment infrastructure. Based on our analysis of rule violations, we derive four new attack vectors, including Free Shopping, Asset Theft, Service Denial, and Gas Abuse. These attacks exploit weaknesses in the real-world facilitator and server implementations and cause severe harm, including direct financial loss to merchants, theft of facilitator-held assets, unbounded sponsor-paid gas/fees, and disruption of payment services. To assess the security of x402 deployments at scale, we propose a semi-automated black-box tool and apply it to 15 major x402 facilitators collectively used by over 60K sellers and 360K buyers. Alarmingly, we find violations in all evaluated facilitators. We responsibly disclosed our findings to the affected parties, who acknowledged the issues and adopted mitigations, including changes by Coinbase. Finally, we complement our controlled testing with an empirical measurement of over 119 million recent Base and Solana transactions, quantifying x402 adoption, facilitator centralization, and ecosystem-level risk indicators.
We audit whether candle-based machine-learning models can turn predictions of cryptocurrency extrema or short-horizon outcomes into positive Binance Spot paper policies after assumed costs. Numerical results come from scripted fixed-seed model runs and deterministic simulators; human-supervised AI agents supported the July 20 evidence-integrity revision through literature retrieval, separately tasked critique, artifact reconciliation, documentation, and source packaging, not trading decisions. The strongest later-period evidence, conditional on extensive predecessor search, is negative: an unchanged ten-pair mandatory-daily selector lost 6.72\% over 19 July cycles at an assumed 31-bps completed-cycle cost, with 3 wins and 16 losses. In short model-specific July evaluations, the validation-selected local-minimum policy returned -1.79\%, while the local-maximum sell-to-cash/re-entry policy underperformed continuous holding by 2.80\%; their gross mean advantages of 11.11 and 12.21 bps were below even the 21-bps stress. A Gurgul-inspired, OHLCV-only daily adaptation attained minimum/maximum ROC AUC of 0.874/0.896 but average precision of only 0.134/0.116 and lost 44.30\% over seven cycles, versus -41.20\% for buy-and-hold. A forensic audit also downgraded an earlier One4All "30-day holdout": its dates had influenced prior architecture work, its four-hour outcome horizon was not purged at split boundaries, it used same-close entry, and its raw result directories were absent. Across the tested, mostly exploratory protocols, event-ranking performance did not establish positive executable policy value. Every operational decision remains NO\_TRADE.
Agentic commerce protocols such as AP2 and ACP define mechanisms for secure agent-initiated transactions but do not provide interoperable, tamper-evident auditability or verifiable temporal ordering of events across heterogeneous domains. This paper addresses these gaps by proposing a verifiable global event timeline for agentic commerce, constructed from four core components: canonical event schemas that enforce deterministic serialization, deterministic batch formation ensuring reproducible ordering without reliance on synchronized clocks, Merkle-based append-only commitments providing logarithmic-cost inclusion proofs, and blockchain anchoring establishing a tamper-evident temporal backbone. Building on this infrastructure, we introduce a cryptographically signed fraud marker that binds risk labels to anchored evidence through an unforgeable provenance chain, and a dataset lineage model enabling reproducible, tamper-evident AI training pipelines. Empirical results from a prototype implementation demonstrate: Merkle tree construction processes 50,000 events in 47 milliseconds; end-to-end verification completes in under 0.013 milliseconds regardless of batch size; inclusion proof sizes grow logarithmically from 320 bytes at 1,000 events to 512 bytes at 50,000 events; and Merkle-based verification outperforms linear scan by 14.4x at 50,000 events.
Gouher Ahmed, Hamza Naim, Aqila Rafiuddin, Mohammed Nizamuddin · 5 authors
This study deals with the performance analysis and volatility estimation of conventional indices including Dow Jones, S&P 500, Brent Oil, Crude Oil and Gold and cryptocurrencies including Bitcoin and Ethereum for the period January 3, 2011 to November 26, 2021 for all of the indices except Ethereum for which the period chosen was from March 10, 2016 to November 26, 2021 due to late incorporation of the cryptocurrency. The stationarity, heteroscedasticity, and serial correlation of the data were considered. Time series regression using the GARCH model is applied for performance analysis and volatility estimation. GARCH (1, 1) estimates show the high performance of cryptocurrencies over the conventional indices, except Gold, which was insignificant, with Ethereum followed by Bitcoin being the most volatile among the different indices. However, Gold remains inert in response to the different indices. However, although the cryptocurrencies add to the country’s revenue, thus minimizing the deficits, there should still be proactive policies and practices to prevent the exploitation of stakeholders, especially for the sake of minority ones.
본 연구는 비트코인과 동북아시아 주식시장(한국, 중국, 일본) 간 동태적 상호의존성을 분석한다. 이를 위해 VAR 모형의 충격반응함수와 Diebold and Yilmaz(2009)가 제안한 전이효과 모형을 이용하여 금융시장 간 파급효과를 측정했다. 또한 코로나19 팬데믹의 영향을 분석하기 위해 분석 기간을 코로나19 이전, 코로나19 기간, 코로나19 이후로 구분했다.<br/> 주요분석 결과는 다음과 같다. 첫째, 코로나19 이전 기간에는 비트코인과 주식시장 간 연관관계가 제한적인 것으로 나타났다. 둘째, 코로나19 기간에는 금융시장 불확실성 확대와 글로벌 유동성 증가로 인해 비트코인이 주식시장에 미치는 전이효과가 크게 확대됐다. 셋째, 코로나19 이후 기간에는 연관관계가 코로나19 기간보다는 완화됐으나 코로나19 이전 기간보다는 높은 수준을 유지했다. 이는 점진적으로 비트코인이 주식시장과 통합되고 있음을 시사한다. 한편, 중국 주식시장의 경우 가상화폐 규제로 인해 비트코인의 파급효과가 상대적으로 제한적으로 나타났다.
Edison Andres Arteaga Lopez, Gustavo Ramírez-González, Andrea Sabbioni, Carlos A. Astudillo
Abstract Distributed ledger technologies (DLT) can enhance trust and auditability in the Internet of Things (IoT). Among them, IOTA has been specifically designed to support machine-to-machine interactions and IoT data anchoring through scalable DLT architectures. However, their integration with Low-Power Wide-Area Networks (LPWANs) remains limited due to device constraints, strict timing requirements, and the operational costs of on-chain transactions. The transition from the fee-less Stardust to the fee-based IOTA Rebased model introduces explicit transaction costs, questioning the viability of continuous IoT data anchoring. IOTA provides a suitable platform to examine the challenges of integrating distributed ledger technologies with LPWAN-based IoT systems. Its transition to a fee-based execution model raises important questions regarding cost predictability and performance in continuous data anchoring scenarios, particularly under the constraints of resource-limited and latency-sensitive environments. This article investigates the practicality of the execution and payment model introduced by IOTA Rebased for IoT scenarios requiring continuous data notarization. We provide an empirical evaluation of continuous IoT data notarization on the public IOTA Rebased Mainnet and characterize the performance implications on edge-oriented deployments, including resource-constrained and resource-rich devices. We implement a notarization oracle that ingests LoRaWAN uplinks from The Things Network (TTN), canonicalizes payloads, generates SHA-256 commitments, and records them on-chain through reusable notarization objects. The oracle enables continuous anchoring of IoT telemetry while minimizing transaction overhead through object reuse. Two 24-h experimental campaigns compare a notarization oracle on resource-constrained and resource-rich hardware under periodic workloads. Results show consistent steady-state gas consumption for UPDATE operations, indicating that object reuse enables stable on-chain cost behavior in IOTA Rebased regardless of the deployment platform. From a performance perspective, both environments achieve stable execution; however, the resource-constrained edge deployment exhibits higher median and tail latency, alongside tighter memory margins compared to the resource-rich centralized baseline. These findings confirm the feasibility of deploying notarization services on constrained edge infrastructure under the new fee-based model.
Diky Paramitha, Etik Ipda Riyani, Nadhira Hardiana, Kan Wen Huey
Bitcoin has a tendency of price volatility that is much higher than other cryptocurrency assets, this makes a very significant difference from other financial assets that can go beyond conventional market logic thus creating a major obstacle in risk management. This study aims to dissect the extreme anomalies of bitcoin trading volume against the volatility of Bitcoin returns. Using a quantitative time series approach, the study analyzed monthly data on bitcoin price and trading volume using Bitcoin prices in the period February 2015 to December 2025. We assess volatility using the GARCH-X model to introduce trading volume as an exogenous variable. The basic GARCH shows significant volatility persistence, indicating a clustering of high volatility in Bitcoin's returns. This finding results that trading volume is not just a static transaction number but reflects a very crucial information proxy. Every movement of trading activity generates new signals in which aggressive price react. Trading volume is also highly correlated with the volatility of returns, although the volatility of the model indicates the need for careful interpretation. Bitcoin's volatility is not solely due to historical volatility dynamics, but also the impetus from trading activity, highlighting the need to consider accurate volatility modeling in the digital asset market. This research adds value by embedding trading volumes into the GARCH model to evaluate its contribution in explaining Bitcoin's volatility through empirical insights for investment decisions and risk management in the cryptocurrency market
Michael Neubert, Wolfgang Rams, Patrick Gruhn, Marcel Lötscher
Perpetual futures (often called perpetual swaps) are the dominant crypto-derivatives instrument. They replicate the economic exposure of a futures contract without an expiry date. They replace maturity-based convergence with a funding mechanism that transfers cash flows between longs and shorts, typically every eight hours. This paper explains how perpetuals evolved from early proposals for non-maturing futures into a standardized crypto market instrument, and why key design choices changed over time. It synthesizes recent theoretical and empirical research on funding design, pricing, and arbitrage intuition, market microstructure, liquidation risk, and regulation. Finally, this study proposes a research agenda organized around funding design, constrained arbitrage, transparency, decentralized exchange design, policy, and legal classification, because recent U.S. and EU developments show that the same economic structure may be characterized as a futures contract, swap, CFD-type instrument, or other derivative depending on statutory definitions, venue design, and supervisory interpretation. This paper proposes the following definition: a cryptocurrency perpetual is an open-ended, margin-based derivative that gives synthetic long or short exposure to an underlying crypto asset and replaces expiry-based settlement with periodic funding payments that anchor the contract price to a reference spot price.
This study examines the transformation of financial transactions under the influence of artificial intelligence (AI) systems and distributed ledger technologies (DLT/blockchain). The European Union, through the implementation of Regulation (EU) 2024/1689 (the AI Act), introduces a horizontal, risk-based regulatory framework specifically related to applications concerning credit-risk assessment, fraud prevention and the automated provision of investment recommendations. In parallel, the recent revision of the EU framework on liability for defective products strengthens the protection of injured parties against digital products and software incorporating AI, while the decision not to advance a specific horizontal directive on non-contractual AI liability underscores the importance
This dataset accompanies the paper An Architectural and Empirical Study of Root-Only Zero-Knowledge Verification and contains the scripts, intermediate artifacts, and published results used to reproduce the empirical evaluation. The repository is organized around two experiment groups: Blockchain-Side Deployment and Verification: deployment and Groth16 proof verification on Ethereum Sepolia and zkSync Sepolia, including contract sources, Merkle-tree inputs, Groth16 proofs, and blockchain measurement CSVs and figures. ZKP proving and off-chain verification: Constraint-count comparison — Groth16 R1CS constraint counts and expanded PLONK gate counts for Merkle-tree depths 5–15, with measurement scripts and summary CSVs/figures. Proving-time comparison — off-chain Groth16 and PLONK proving benchmarks across depths 5–15, including proving scripts, generated witness/proof/key artifacts, and benchmark CSVs/figures.
Autonomous AI agents now hold funds, delegate authority to other agents, and transact at machine speed; the governance apparatus meant to constrain them—policies, audits, compliance—remains documentation-based and human-latency. This mismatch cannot be closed by better monitoring or filtering: compliance must become a runtime, compositional, proof-carrying property of computation itself. We call the resulting discipline computational jurisprudence. This article surveys the four literatures the discipline must synthesize: object-capability security; verifiable, proof-carrying, and zero-knowledge computation; policy-as-code and computational law; and agentic AI with its emerging payment protocols. Each supplies a mature mechanism the others lack; none supplies a complete normative substrate. The synthesis is organized in three pillars: (i) a delegation calculus under which authority can only attenuate as it propagates between agents; (ii) runtime compliance proofs, a three-tier evidence regime (attested, optimistic, and zero-knowledge); and (iii) sealed delegation chains with graduated attribution, which reconcile the privacy of capability-based authority with the accountability that adjudication requires. A case study on agentic payment protocols grounds the architecture and reports first measurements: capability verification versus a centralized policy decision point, end-to-end enforcement on the x402 payment path, and accumulator-based revocation. Seven open problems define the research agenda.
Although local public finance regulation has received substantial attention within fiscal decentralization and public financial management research, comparative analyses of its institutional configuration as an integrated regulatory regime remain limited. This study aims to examine the institutional design of local public finance regulation across European countries, analyze how regulatory standards, supervisory institutions, monitoring mechanisms, and enforcement instruments interact to strengthen regional governance, and formulate policy implications for Indonesia’s fiscal decentralization reforms. A qualitative comparative government design was employed through a systematic literature review. The study analyzed documentary evidence from 21 European countries purposively selected from Local Public Finance: An International Comparative Regulatory Perspective (2021), supplemented by Eurostat Government Finance Statistics, the European Commission Fiscal Rules Database, and the OECD Tax Autonomy Database. Data were examined using qualitative content analysis involving coding, categorization, cross-country comparison, and thematic interpretation. The findings indicate that effective local public finance regulation depends not merely on the presence of numerical fiscal rules but on the institutional integration of regulatory standards, supervisory bodies, monitoring mechanisms, and enforcement arrangements within coherent governance systems. Regulatory configurations also vary according to constitutional structures, administrative traditions, and fiscal decentralization models, resulting in diverse approaches to maintaining fiscal sustainability and regional accountability. The study concludes that effective regional financial governance requires balanced institutional arrangements that combine local fiscal autonomy with robust oversight, transparency, accountability, and regulatory coordination. These findings contribute to the literature on regulatory governance, comparative government, and fiscal federalism by conceptualizing local public finance regulation as an integrated governance regime rather than a collection of isolated fiscal controls. They also provide practical implications for Indonesia by emphasizing the need to strengthen supervisory capacity, fiscal transparency, enforcement consistency, and intergovernmental regulatory coordination in local financial governance.
Open access
Local Government Finance and Decentralization
Fiscal Policies and Political Economy
Sustainability, Governance, and Employment Studies
Blockchain technology, originally devised to support the peer-to-peer transfer of Bitcoin, has evolved into a multipurpose digital infrastructure with far-reaching implications for business and finance. This paper undertakes a conceptual and exploratory examination of how blockchain is reshaping financial services, corporate governance, and commercial transactions. Drawing upon secondary literature, industry reports, and case illustrations, the study investigates blockchain applications across banking, cross-border remittances, supply chain finance, trade finance, capital markets, insurance, and decentralized finance (DeFi). It also discusses the enabling features of blockchain — decentralization, immutability, transparency, and smart contracts — that differentiate it from conventional centralized systems. The paper highlights the strategic benefits accruing to firms that adopt blockchain, including reduced transaction costs, faster settlement, enhanced traceability, and improved trust among counterparties, while also identifying barriers such as regulatory ambiguity, scalability constraints, energy consumption, and limited interoperability. The discussion synthesizes findings from extant studies to present an integrated view of blockchain’s transformative potential and its practical limitations. The paper concludes that while blockchain is unlikely to replace traditional financial infrastructure entirely in the near term, its selective and hybrid adoption is poised to redefine business processes, financial intermediation, and value exchange across industries.
Contemporary AI governance regimes (GDPR, the EU AI Act, NIST AI RMF) operate declaratively: they mandate outcomes but provide no computational mechanism by which compliance can be verified at execution time without exposing the underlying data. This produces a structural verification asymmetry, the cost of proving integrity is borne by the auditor, who must inspect raw data the operator cannot lawfully or commercially disclose. We propose ZEGA (Zero-Knowledge Execution Governance Architecture), a governance layer in which execution logs are committed cryptographically at capture time, anomaly predicates are evaluated inside zero-knowledge circuits, and regulators verify a succinct proof of integrity without observing a single record. We formalize an Integrity Debt metric ID, quantifying accumulated unverified execution mass, and specify an empirical pipeline over Google BigQuery public datasets (GitHub Archive, 2011–present; >8 billion events) that operationalizes ZEGA’s anomaly-filtering and commitment stages at planetary scale. Executed over a 30-epoch window of 112 million real execution events, the pipeline demonstrates that predicate evaluation is tractable within commodity cloud infrastructure at a stable anomaly base rate of 0.0137% (CV = 0.269). A seven-year longitudinal extraction (2020–2026; 25.4 million events) shows execution volume persistently concentrated in the top decile of actors (66.2% mean share, CV = 0.097), establishing that the baseline ZEGA predicates are calibrated against is structural, not seasonal. We further execute a live zero-knowledge instance over a committed one-hour epoch (45,674 actors), proving the anomaly-rate predicate with a real BN128-curve argument that discloses a single verdict bit and survives forgery and tamper tests, establishing ZK verification with proof size O(log N) and verification time independent of N. ZEGA converts governance from attestation to mathematics: the regulator’s question changes from “show us your data” to “show us your proof.”
When a person creates with an AI system, they continually make decisions that carry meaning but have no verbal form: this shot belongs before that one; this phrase resolves that tension. These creative micro-decisions are a distinct training signal with no linguistic equivalent, and at scale they reveal an emergent, co-authored "hybrid tongue" — a grammar of "what belongs next to what" that neither party states explicitly. Because such grammar can expand a model's generative capacity faster than natural language describes it, it drives a widening "comprehension gap": capability that outruns human interpretability, and human contribution absorbed without attribution. Both are trustworthy-AI failures, and this paper argues they are correctable only on a decentralized substrate, where persistence, provable attribution, incentive, and governance are guaranteed rather than merely asserted. This is a position paper. It contributes (i) a falsifiable model of the hybrid tongue, positioned against the emergent-communication and human-feedback literatures; (ii) the Seam-Frame Index, a capture mechanism that records creative decisions (not their private reasons) and whose trust properties are supplied by persistent conversation objects (vCons), decentralized-science patterns (DeSci), decentralized-finance primitives (DeFi), and DAO governance, with decentralized identifiers and verifiable credentials underpinning a per-decision credit ledger for which a protocol sketch and threat model are given; and (iii) two governance instruments — an operationalized Comprehension Gap Meter and that ledger. The same gap is shown opening in the machine economy and across the embodiment bridge of decentralized physical AI and bidirectional digital twins, and the pattern is argued to be substrate-wide. Across all of it the event is identical: an intelligence assembling the first letters of its own language library — by default, without human consent. Decentralized attribution and gap-measurement are how that assembly is made auditable, creditable, and consented-to by design. Independent preprint. Follows IEEE formatting conventions but is not peer-reviewed by, submitted to, accepted by, or affiliated with IEEE.
Muhammad Habibi, Mirza Agung Rahmatullah, S Huda, Achmad Alif Nurbani
Perkembangan ekonomi digital telah melahirkan berbagai bentuk aset digital, seperti cryptocurrency dan Non-Fungible Token (NFT), yang memiliki nilai ekonomi tinggi dan berpotensi dimanfaatkan dalam hubungan keperdataan. Penelitian ini bertujuan untuk menganalisis kedudukan hukum cryptocurrency dan NFT dalam perspektif hukum perdata Indonesia sebagai objek hak kebendaan serta mengkaji pengaturan dan perlindungan hukum terhadap penggunaannya sebagai objek jaminan utang. Penelitian menggunakan metode hukum normatif dengan pendekatan perundang-undangan, konseptual, dan perbandingan. Data yang digunakan berupa bahan hukum primer, sekunder, dan tersier yang dianalisis secara kualitatif melalui metode yuridis normatif. Hasil penelitian menunjukkan bahwa cryptocurrency dan NFT secara konseptual memenuhi unsur sebagai benda bergerak tidak berwujud karena memiliki nilai ekonomi, dapat dimiliki, dikuasai, dialihkan, dan menjadi objek hubungan hukum. Kedua aset digital tersebut juga memenuhi persyaratan dasar sebagai objek jaminan utang. Akan tetapi, sistem hukum kebendaan dan hukum jaminan di Indonesia belum memberikan pengakuan dan pengaturan yang tegas mengenai kedudukan cryptocurrency dan NFT sebagai objek jaminan kebendaan. Ketiadaan regulasi khusus menimbulkan ketidakpastian hukum terkait mekanisme pengikatan, pendaftaran, penilaian, penguasaan, dan eksekusi aset digital. Oleh karena itu, diperlukan pembaruan hukum yang mampu mengakomodasi perkembangan teknologi digital guna memberikan kepastian hukum, perlindungan hukum, dan kemanfaatan bagi para pihak.
Cryptocurrency is no longer that of a topic solely for traders and tech enthusiasts, as crypto ETFs have worked their way into mainstream retirement accounts, bringing with them many questions to financial planners. The question this study addresses is whether small Bitcoin and Ethereum ETF allocations actually improve the risk-adjusted performance of a traditional balanced retirement portfolio. To find out, five different portfolio constructions were tested using real ETF return data, with performance measured across Sharpe ratio, Sortino ratio, maximum drawdown, and correlation, all with quarterly rebalancing built in. Every portfolio that included cryptocurrency outperformed the standard baseline on risk-adjusted return metrics, though drawdown did increase as the allocation grew. What this tells us is that small, structured cryptocurrency allocations have the potential to improve retirement portfolio performance for the right investor, but suitability still needs to be worked out on an individual basis, something financial planners can take directly into their practice.
Junhong Liu, Qinfei Long, Alex Pengfei Zhao, X Zhong · 7 authors
Multi-region unit commitment with reserve sharing requires coordinated optimization across jurisdictionally distinct system operators, exposing sensitive cost curves, topology, and dispatch decisions to inference attacks. The accelerating progress of quantum computing further compounds this threat. As quantum hardware matures, current classically-encrypted data flow becomes vulnerable to retrospective decryption. To enable post-quantum-secure distributed optimization, we propose a customized Benders decomposition-based approach with the global summation structure to share aggregated cuts and variables. By exploiting this structure, we further develop a multi-layer quantum-resilient secure aggregation protocol comprising additive masking for information-theoretic content privacy, affine variable transformation hiding individual sensitive data flows, and reveal-bound lattice-based zero-knowledge proofs providing resilience against active adversaries. Simulation results show that the proposed approach achieves the mean suboptimality of 0.09%-0.22% with lightweight computational overhead, recovers up to 51% of system cost via inter-regional reserve sharing, and imposes no measurable cost-quality trade-off, whereas the noisy ADMM degrades monotonically under tightening privacy budgets and becomes structurally infeasible on combinatorially dense systems.