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.
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.
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.
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.
With the rapid advancement of decentralized finance (DeFi), security incidents related to cryptocurrency have become increasingly prevalent. After such incidents, attackers typically attempt to rapidly move stolen assets, concealing the origin of illicit funds and ultimately converting them into fiat currency. However, existing anti-money laundering (AML) methods struggle to cope with the semantic complexity of DeFi transactions. They either rely heavily on low-level token transfers, or perform protocol-agnostic money flow analysis, failing to capture the high-level intent of transactions. In this paper, we propose AMLGuard, a semantic-aware AML framework for account-based blockchains. AMLGuard tracks illicit fund flows from known malicious addresses by performing semantic analysis on complex DeFi transactions, enabling accurate and continuous laundering tracking. Given a complex transaction, AMLGuard combines static rule-based analysis with retrieval-augmented large language model (LLM) reasoning to infer implicit DeFi semantics, transforming raw transaction data into high-level semantic representations. Furthermore, for cross-chain transactions where laundering intent is not explicitly exposed, AMLGuard parses transaction parameters and performs argument parsing to recover cross-chain semantics, enabling seamless tracking across ledgers. Based on the inferred semantics, AMLGuard abstracts each transaction into a DeFi Semantic Unit (DSU). We evaluate the effectiveness of AMLGuard on 82 real-world laundering cases, involving illicit assets worth over $1 billion. Specifically, AMLGuard reconstructs compact illicit fund-flow topologies with destination precision of 94.4% and 87.6%, while achieving the highest address recall of 98.4% and 95.8% and destination recall of 94.1% and 93.8% on single-chain and cross-chain datasets.
Bitcoin’s Proof-of-Work mechanism is energy intensive, exceeding the electricity consumption of a medium-sized country. As the adoption accelerates, it become a concern. Most studies analyzed its energy consumption, emissions, and price in isolation. This study examines the relationship between the energy consumption and energy mix of Bitcoin and its market performance, moderated by quality of regulation, using a time-series of secondary data from reputable resources e.g. Cambridge Bitcoin Electricity Consumption Index,, the Worldwide Governance Indicators, etc. Regression analyses are employed to test the hypotheses. Eight of nine null hypotheses failed to reject. However, energy consumption was found to have a significant positive relationship with market return. It is, however, likely that this finding captures shared underlying drivers of Bitcoin’s price and its energy consumption, as well as possible reverse causality. Energy mix was found to have no significant effect on the three alternative outcomes, aligned with the fungibility of Bitcoin. Furthermore, regulatory was found not to significantly moderate also likely due to the narrow variation in the Indonesia’s scores during the study period. The study identified that markets do not reward sustainable mining with a market premium, implying that the transition towards renewable-powered mining in Indonesia requires more policy intervention.
The rapid development of the Fourth Industrial Revolution (IR 4.0) and Web3 has catalyzed digital transformation in the education sector through the convergence of Artificial Intelligence (AI) and the metaverse. However, most existing initiatives remain isolated and passive, lacking adaptive learning capabilities. These initiatives also face cross-platform interoperability constraints, cybersickness, gaps in educator readiness, and ethical concerns regarding biometric data privacy. In view of this, this study was conducted with the objective of constructing an integrated conceptual framework, Edu-AIMeta, that links technological dimensions with learning theories, critically analyzing implementation challenges, and proposing sustainable cyber-governance strategies. To achieve these goals, this study employs a conceptual-integrated literature review design by critically analyzing and synthesizing theoretical perspectives from 22 articles published between 2022 and 2026 across the Scopus and Web of Science (WoS) databases. The research findings outline three primary dimensions of integration success: the AI cognitive engine, the spatial metaverse environment, and user adoption and competence, particularly among Generation Z students and educators. Moving forward, this paper recommends the development of an inclusive meta-governance framework through the implementation of open-source standards, the formulation of ethical guidelines for biometric data protection, and the provision of structured immersive pedagogical training programs to ensure an equitable, secure, and sustainable future educational ecosystem.
The rapid digital transformation has made verifiable professional digital skills essential for workforce competitiveness, yet traditional resumes and certificates suffer from high fraud rates (50–70%), lengthy manual verification, and failure to recognize non-traditional pathways. This paper investigates SSI-, DID-, and W3C VC-based digital skills wallets as a solution to restore cryptographic trust in HR recruitment. Adopting the Design Science Research Methodology (DSRM), we conducted a PRISMA 2020 systematic review of 42 high-quality sources (2022-early 2026). The review established the technical maturity of SSI/VC technologies for micro-credentials and Learning and Employment Records (LERs) while revealing critical gaps in enterprise HR integration and emerging-market (particularly China) applications. We designed a modular, blockchain-optional digital skills wallet architecture fully compliant with W3C Verifiable Credentials Data Model v2.0, 1EdTech Comprehensive Learner Record, and China’s RealDID national identity infrastructure. The artifact supports lifelong credential aggregation, selective disclosure via BBS+ zero-knowledge proofs, and instant cryptographic verification (<3 seconds). The design was demonstrated through three China-specific recruitment use cases and empirically validated via a mixed-methods survey with 42 HR professionals and recruiters from major technology companies in Beijing, Shanghai, Shenzhen, and Guangzhou. Results indicated strong perceived utility: credential fraud was rated a major issue (M = 4.69), the wallet was expected to substantially reduce verification time (M = 4.57) and increase confidence in candidate claims (M = 4.45), with positive willingness to pilot or adopt (M = 4.19), especially when integrated with RealDID. These findings demonstrate that SSI-based digital skills wallets can near-eliminate resume fraud, collapse verification from weeks to seconds, expand talent pools through skills-first matching, and ensure privacy-preserving selective disclosure while aligning with national digital identity strategies. The study contributes a replicable DSRM template bridging verifiable credentials and skills-based talent management literatures, together with practical recommendations for HR leaders, ATS integration, and policy development.
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 three experiment groups: On-chain 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. 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. Shared setup files include Circom circuits, Merkle-tree preparation scripts, circuit inputs, and compiled circuit artifacts. Most of the generated data is produced by the provided scripts and does not need to be included separately if the reproduction pipeline is documented.
Open access
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Formal Methods in Verification
Physical Unclonable Functions (PUFs) and Hardware Security
Secure, interconnected, and compatible data sharing of Electronic Health Records (EHRs) across healthcare domains is essential for timely patient care and improved adaptability in healthcare infrastructures. Current challenges must be addressed, including centralization threats, fragmented standards, and threats from quantum computing. This paper proposes a blockchain-based EHR framework using post-quantum cryptography and HL7 FHIR standards for secure, interoperable data sharing. It employs smart contracts for patient-centric access control and HotStuff BFT consensus, achieving 928 TPS with 2.1-second finalization. Zero-knowledge proofs enable privacy-preserving authentication, and dynamic accumulators improve revocation storage efficiency by 89%. On a 20-node testbed, the system sustains 620 TPS at 500 ms latency, with under three-second access grants and 95% storage efficiency via cryptographic pointers. Compared to current systems, it offers 20× higher throughput and resists quantum threats. Multi-hop exchange across three hospitals reduced normalization efforts by 40%. Comprehensive assessment on the system outcomes reveals that our framework significantly enhances security, scalability, and interoperability for decentralized healthcare networks.
Abstract Distributed ledgers – decentralized databases maintained by network consensus – are often modeled as directed acyclic graphs (DAGs) to capture the causal structure of data addition. Although blockchain systems like Bitcoin use linear chains, alternatives such as tangle in IOTA employ random DAGs. In such mechanisms each new transaction approves multiple predecessors selected through a randomized process. Prior work has established a fluid-limit approximation of the tangle’s growth, governed by a delay differential equation. In this paper we go beyond the fluid limit by analyzing the next-order behavior. We show that the fluctuations around the deterministic limit converge to a Gaussian process and derive a stochastic delay differential equation (SDDE) that describes this next-order approximation.
Smart contracts are programs that automatically enforce some kind of agreement between parties, without the need of a trusted third party. Since they frequently deal with large sums of money (in the form of crypto assets) it is critical that smart contracts attain precisely to their specification and do not have any unexpected behaviour. In this thesis, I will present two lines of research, one related to developing smart contract languages for the UTXO blockchain model, and the other related to the formalization of MEV attacks.
Federated Learning (FL) enables collaborative model training across decentralized participants without sharing raw data. However, existing FL systems remain vulnerable to Byzantine attacks and suffer from a lack of accountability, verifiability, and economic incentives for honest participation. We present BFL-Guard, a novel blockchain-orchestrated federated learning framework integrating: (i) zk-SNARK-based zero-knowledge gradient proofs, (ii) an on-chain Byzantine-tolerant aggregation smart contract, and (iii) a tokenized incentive protocol (FedToken). BFL-Guard stores model checkpoints as IPFS hashes anchored on Ethereum, ensuring tamper-evident auditability. Experiments on CIFAR-10 and Shakespeare benchmarks demonstrate 95.2% and 87.6% accuracy in IID and Non-IID settings, surpassing all baselines while converging 12.4% faster even under 30% Byzantine injection.
Elsir Ali Saad Mohamed, Khalid Ibrahim Abdelaziz Ishag, Omnia Salem, Ahd M. M. Abudraz · 8 authors
The convergence of blockchain technology and the Metaverse is redefining digital media ownership and distribution. Drawing on survey data from 613 digital media professionals and a qualitative synthesis of literature (2023–2026), this study examines how blockchain-based mechanisms—specifically non-fungible tokens (NFTs), smart contracts, and decentralized identity (DID) solutions—are associated with creator sovereignty and platform interoperability. Using a moderated chain mediation model within a socio-technical systems framework, the analysis shows that blockchain integration is associated with lower perceptions of platform dependency. This association is linked to a sequential pathway whereby higher decentralized governance is associated with lower intermediary control, which in turn is associated with higher creator monetization autonomy. Connectedness to decentralized protocols differentially shaped these processes: at the technical level, stronger protocol integration strengthened the negative association between blockchain adoption and intermediary dependence; however, at the governance level, a paradoxical pattern emerged, whereby stronger decentralization was associated with higher perceived governance overload in the context of algorithmic decision-making. By disentangling the technical and governance pathways, this study extends current understanding of digital media ecosystems beyond simple use-outcome associations. The findings highlight the importance of considering individual differences in digital literacy and institutional trust when designing blockchain governance frameworks. We conclude that blockchain is not merely an incremental improvement but a necessary architectural requirement for a resilient and equitable Metaverse, contingent upon addressing the risks of surveillance federalism and the digital divide.
The security and privacy of blockchain data have become critical research challeSimilarly, the full-function accounting node verifies the validitynges. While numerous approaches have been proposed to address these concerns, many existing schemes suffer from high computational complexity or excessive verification latency. To bridge this gap, this paper presents a secure and privacy-preserving blockchain data transaction verification system. By integrating the Paillier cryptosystem with a zero-knowledge range proof protocol, the proposed system ensures the confidentiality of transaction amounts and participant identities, simultaneously achieving strong anonymity and conditional traceability for users. Moreover, fully functional accounting nodes support efficient ciphertext-domain balance updates, eliminating the need for decryption during accounting operations. Experimental evaluation confirms the practicality and high performance of the proposed system.