A Universal, Options-Free, One-Byte Market-State Primitive: Cross-Asset Transfer, Distributional-Novelty Detection, and Privacy-Preserving Federation Randolph James Ferlic, M.D. and Kimberly Kate Ferlic (Fieldstone Analytics, LLC, Austin, TX, USA) Preprint ¡ Zenodo DOI: 10.5281/zenodo.22116173 ¡ CC-BY 4.0 ¡ Community: spiral-domain-encoder-campaign Abstract A companion study established that a fixed class-discriminant encoder â which reduces a window of a multivariate stream to a single 8-bit token â is a near-lossless detector of market stress across asset classes, but a taxed classifier and a null forecaster. This study asks, under strict pre-registration, whether that detector becomes a *universal, deployable primitive*, and finds that it does, along five axes, with an honest boundary preserved throughout. (1) The codebook is universal: fit on equities alone, it detects stress zero-shot across cryptocurrency, commodities, emerging-market funds, credit, and foreign exchange at a median AUC of 0.84, within 0.01 of a bespoke per-asset codebook, because the calm-to-stress discriminant direction is nearly identical across asset classes (median cross-asset cosine 0.94). (2) The token detects distributional regime-change that volatility structurally misses â the one place it beats volatility â and is an orthogonal channel that improves a volatility-only stack by +0.18 AUC on a mixed target. (3) It generalizes to credit and rates (pooled AUC 0.91) and to currency crosses (0.80), including markets with no options index. (4) It is cheap at scale and low-data: a genuine one-byte-on-the-wire firm-wide dashboard detects systemic stress at 0.92 at 200Ă compression â a 42-instrument universe fits in ~10 kilobytes per year â and a new deployment is usable after ~3 months of calm history. (5) The same one-byte token supports privacy-preserving federation: institutions each sharing one token per day match full-data systemic-detection utility while their individual positions are unrecoverable even to a non-linear, colluding, market-informed adversary (incremental reconstruction R² â 0.01). All headline results survive a permutation-placebo leakage test, moving-block bootstrap confidence intervals, and robustness to split, seed, stress-label, and a strict recent holdout. Every negative is reported, and two honest scope refinements are disclosed: a formal differential-privacy guarantee is event-level, not stream-level, and portfolio membership is coarsely inferable while positions are not. Highlights ¡ Universal codebook â one equity-fit codebook detects stress zero-shot across every asset class (median 0.84, transfer loss ~0.01, 22/23 targets); mechanism = a shared cross-asset stress direction (cosine 0.94). ¡ A capability volatility lacks â the token detects distributional (shape) regime-change where trailing volatility is at or below chance; an orthogonal channel that complements any GARCH/VIX stack. ¡ Coverage â credit/rates (pooled 0.91) and FX/carry white-space (0.80), options-free, at one byte per instrument. ¡ Compression-at-scale â a 1-byte-on-the-wire firm-wide dashboard at AUC 0.92, 200Ă compression, ~10 KB/instrument-year; detection-sufficient encoder â 590 multiply-accumulates and < 3 KB (microcontroller-class). ¡ Low-data cold-start â usable after ~3 months of calm data; saturates within ~2 years; train on a trailing window. ¡ Privacy-preserving federation â full-data-equivalent systemic detection with individual positions non-invertible even under a strong adversary; optional event-level differential privacy; manipulation-robust median aggregation; per-channel attribution; a yield-curve-shape token. ¡ Information-theoretic characterization â detection is a ~1-bit decision while classification is high-bit; competitive with principled two-sample/OOD tests at O(1) online cost. ¡ Honest negatives and hardening â network topology, temporal-token, cross-sectional ranking, and tail-edge results are all reported null; every headline result is leakage-tested (permutation placebo â chance) and confidence-bounded. What this record contains ¡ Manuscript_Paper40.pdf â the manuscript (single-column preprint). ¡ PAPER_40_ZENODO_ARCHIVE.zip â the reproducibility archive: seven pre-registration scopes (frozen outcome bands) covering studies FIN-15 ⌠FIN-45; the deterministic per-study runners and the shared frozen encoder/loader and federation modules; the per-study JSON result summaries behind every figure and table value; the figure-rebuild script; and the eight figures. All paths and identifiers are scrubbed and leak-scanned per the campaign deposit discipline; no raw market data is redistributed. Cite as R. J. Ferlic and K. K. Ferlic, "A universal, options-free, one-byte market-state primitive: cross-asset transfer, distributional-novelty detection, and privacy-preserving federation," Zenodo, 2026, doi: 10.5281/zenodo.22116173. License and patent notice Released under the Creative Commons Attribution 4.0 International License (CC-BY 4.0). Consistent with that license, no patent, patent-application, or other intellectual-property right of the authors is licensed, waived, granted, or otherwise conveyed by this deposit; the methods described â including the single-token class-discriminant encoder, its multi-token product-quantization variant, its unsupervised nearest-centroid-distance monitoring mode, and the privacy-preserving multi-party aggregation of its tokens â are the subject of filed and pending U.S. patent applications. Licensing inquiries: randolphf@fieldstoneanalyticsllc.com. Companion deposits (spiral-domain-encoder-campaign) ¡ Single-token financial market-state monitor (companion study): doi:10.5281/zenodo.22101085 ¡ Single-token industrial sensor substrate: doi:10.5281/zenodo.20854722 ¡ Hardening and generality characterization: doi:10.5281/zenodo.20802759 ¡ Deterministic multi-token token ladder: doi:10.5281/zenodo.22003179 Keywords universal codebook; decision-preserving compression; distributional novelty; federated privacy; differential privacy; systemic risk; market-stress detection; class-discriminant codebook; cross-asset transfer; edge computing; anomaly detection; pre-registration; honest negatives; financial time series; regime detection; credit risk; yield curve; volatility regime; VIX; market surveillance
The rapid diffusion of crypto currency in Nigeria has attracted considerable attention from academics, practitioners, and policymakers. This study investigates the determinants of crypto-currency adoption, market growth, and price dynamics in Nigeria, with a particular focus on financial inclusion, regulatory environment, technological advancement, investor sentiment, and macroeconomic factors. The research objectives are (i) to assess the appeal and growth trajectory of crypto-currencies in Nigeria; (ii) to identify the risk factors that shape their evolution; and (iii) to derive policy-relevant insights for regulators and industry stakeholders. A quantitative approach was employed using quarterly data spanning 2012-2023 (N = 43). Five hypotheses were formulated and tested using a battery of time-series techniques: Granger-causality, unit-root tests, Johansen cointegration, and autoregressive distributed-lag (ARDL) modelling. The proxies for the independent variables were: number of crypto users, transaction volume, and number of exchanges (cryptocurrency adoption); number of regulatory approvals, regulatory clarity, and regulatory support (regulatory environment); internet penetration, mobile-phone adoption, and tech-startup count (technological advancement); social-media mentions, sentiment analysis, and investor-confidence index (investor sentiment); and GDP growth, inflation, and exchange rate (economic factors). Dependent variables included percentage of the population with financial-service access, number of bank accounts, mobile-money adoption (financial inclusion); market capitalization, trading volume, and new listings (crypto-market growth); standard deviation of price returns and frequency of price jumps (price volatility); and number of transactions and users (crypto demand). The empirical findings reveal a complex interplay among the variables. Granger-causality tests indicate bidirectional predictability between crypto currency adoption and financial inclusion, as well as unidirectional causality from regulatory environment, technological advancement, investor sentiment, and economic factors to their respective outcomes (p < 0.05). Unit-root tests confirm stationarity of all series (I(0)), justifying the use of cointegration analysis. Johansen tests detect at least one cointegrating vector for each hypothesis, suggesting long-run equilibria. ARDL models provide nuanced short-run dynamics: a 1 % improvement in regulatory quality raises market growth by 0.98 % (p < 0.001); technological advancement has a modest, borderline-significant short-run effect on adoption (p = 0.09); investor sentiment exhibits a contemporaneous calming effect on volatility followed by a lagged increase (p = 0.04); and economic factors display a near-unit elasticity (0.98, p < 0.001) with crypto demand in the short run but a negative long-run association, implying that sustained economic improvement may reduce cryptoâs appeal. The study concludes that while regulatory clarity, technological infrastructure, and macroeconomic stability are pivotal in shaping the short-run trajectory of the Nigerian crypto market, their long-run impact can be ambivalent. Investor sentiment emerges as a significant driver of price volatility, underscoring the role of behavioural factors in this emerging asset class. The findings underscore the need for a balanced regulatory framework that encourages innovation while safeguarding financial stability, alongside targeted investments in digital infrastructure and financial-literacy programmes.
Liu Jin, Yahya M.H., Saidatunur Fauzi Saidin, Li Lu
Abstract Multivariate cryptocurrency forecasting is challenging because market series exhibit non-stationarity, cross-variable dependence, heterogeneous temporal scales, and abrupt short-term fluctuations. Although Transformer-based forecasting models can capture long-range temporal relationships, directly modeling raw high-frequency sequences may obscure dominant periodic structures and increase computational cost. This study proposes a frequency-guided multi-scale decomposition and patch Transformer, termed FMDP-Transformer, for multivariate cryptocurrency time-series forecasting. First, a frequency-guided multi-scale representation module estimates dominant temporal periods from the Fourier amplitude spectrum and constructs scale-specific representations through period-dependent average pooling. This module is designed to extract multi-scale periodic information and attenuate short-term disturbances rather than to perform explicit anomaly detection. Second, the resulting representation is decomposed into trend and residual components. A lightweight linear projection is used for parsimonious trend extrapolation, while the residual component is divided into overlapping patches and processed by a Transformer encoder to model local and long-range temporal dependencies. The forecasts produced by the two branches are subsequently combined. Experiments on Bitcoin, Dogecoin, and Binance Coin data derived from the G-Research Crypto Forecasting dataset evaluate the model under multiple forecasting horizons. Comparisons with recurrent, decomposition-based, patch-based, inverted-Transformer, and multi-scale forecasting models, together with component ablations and computational-complexity analysis, are used to assess its effectiveness. The results indicate that frequency-guided multi-scale representation, decomposition, and patch tokenization provide complementary benefits for multivariate cryptocurrency forecasting. Nevertheless, the proposed frequency-guided smoothing operation does not explicitly identify statistical anomalies, and abrupt market movements may contain predictive information rather than noise.
Abstract The emergence of cryptocurrencies has presented investors with novel portfolio diversification opportunities. This study investigates the interplay between precious metals and cryptocurrencies, examining their potential for enhancing portfolio returns and mitigating risk. Using daily closing prices from August 2017 to November 2022, we employ an autoregressive distributed lag (ARDL) approach to analyze comovement and causality between these asset classes. Our findings reveal a short-run linkage between Bitcoin, precious metals, and other cryptocurrencies but no long-run cointegration. Notably, gold prices unidirectionally influence cryptocurrency prices, a relationship not observed with other assets. This absence of long-term comovement suggests that precious metal investors can leverage modern portfolio theory to diversify cryptocurrency volatility risk. These results offer valuable insights for investors seeking to optimize portfolios by strategically incorporating cryptocurrencies for improved risk-adjusted returns.
This study proposes a Bitcoin price prediction model utilizing Long Short-Term Memory (LSTM) networks, integrating technical indicators, Reddit sentiment indicators, and on-chain data. The cryptocurrency market, particularly Bitcoin, exhibits extreme price volatility, despite its high profit potential. This volatility stems from a combination of macroeconomic factors, market participant sentiment, and fluctuations in supply and demand within the blockchain ecosystem. Existing literature typically examines only one or two types of dataâwhether technical, sentiment, or on-chainâwithout systematically verifying the complementary effects of integrating these heterogeneous data sources on predictive performance. To address this gap, this study quantitatively analyzes the contribution of each data type by constructing four experimental settings combining technical indicators, Reddit sentiment, and on-chain data based on Bitcoin price movements. Moreover, the proposed LSTM model is benchmarked against Linear Regression (LR), Random Forest (RF), and XGBoost (XGB) under identical experimental conditions. Evaluation metrics, including RMSE, MAE, and MAPE, indicate that while the LSTM model demonstrates superior predictive performance using only technical indicators, the inclusion of both Reddit sentiment and on-chain indicators results in a slight increase in error metrics. Nevertheless, this study emphasizes the potential of capturing the multifaceted characteristics of the market, which are often overlooked with single price-based indicators. It provides an empirical foundation supporting the effectiveness of heterogeneous data integration in future cryptocurrency price prediction research.
A decentralized autonomous organization (DAO) is a novel form of blockchain-based organization designed for collective decision-making. As DAOs emphasize a decentralized, democratic decision-making approach, participation serves as the foundation for their sustainable operation and development. Unfortunately, many DAOs struggle with low participation rates, often falling short of the required quorum. To address this critical issue, an increasing number of DAOs have adopted delegated voting, which allows members to transfer their voting rights to others. However, the impact of delegated voting within the DAO context remains unknown. By leveraging variation in the adoption of delegated voting across DAOs, we find that delegated voting increases membersâ participation in proposal voting and enhances decision quality. Our results further show that delegated voting stimulates greater participation in proposals with higher participation costs, including those that are more complex, urgent, or operational in nature. However, in the long term, delegated voting also leads to greater voting power concentration and reduces engagement from both new and active voters, potentially harming sustained participation and the growth of the DAO community. Overall, our findings highlight the need for DAOs to balance the short-term gains from higher participation with the potential long-term risks to decentralization.
Relationships involving blockchain organizations are largely governed by special rules that form the lex cryptographia. This regulatory framework is represented by the code of smart contracts and blockchain protocols. Regulating the legal status of digital legal entities, it acts as a local legal act, and in the field of private international law, as a supranational, conditionally autonomous legal or sub-legal system. In the first case, the lex cryptographia can be classified as a âthirdâ legal order, developing alongside the international and domestic legal systems. In the second case, it is a system of rules that operates solely within the applicable legal order, based on the principles of autonomy of the partiesâ will and freedom of contract.
Zaid Tahat, Ahmad Alomari, Ibrahim Al-Radaideh, Adham Taher Alessa ¡ 7 authors
This study examines the mediating role of investor trust in the relationship between perceived blockchain integration and perceived stock market efficiency within the Amman Stock Exchange (ASE). The Amman Stock Exchange (ASE), established in 1999, is the sole securities exchange in Jordan and one of the leading emerging markets in the Middle East and North Africa (MENA) region. Drawing on technology acceptance theory, trust theory, and market efficiency theory, the research develops and tests a dual-pathway model wherein perceived blockchain integration relates to perceived market efficiency both directly and indirectly through investor trust. Using structural equation modeling with data collected from 400 market participants, the findings reveal that perceived blockchain integration is significantly and positively associated with investor trust (β = 0.849, p < 0.001) and with perceived stock market efficiency (β = 0.448, p < 0.001). Importantly, investor trust partially mediates this relationship (β = 0.380, p < 0.001), confirming the dual-pathway impact. Among blockchain dimensions, security demonstrates the strongest effect on both investor trust and market efficiency. The study contributes to the emerging literature on blockchain in financial markets by empirically validating the psychological mechanisms through which technological innovations translate into more favorable perceptions of market functioning. For market regulators and exchange administrators, the findings suggest that comprehensive blockchain implementation strategies should address both technological deployment and trust-building initiatives to strengthen favorable investor perceptions of market efficiency in emerging markets.
Type of the article: Research ArticleAbstractThe blockchain financial system allows users to send money fast without any border restrictions. However, the same structure of the blockchain may be used as a means of laundering money. This paper assesses the relationship between the complexity of transaction networks and the likelihood of their illicit nature within the public Elliptic Bitcoin benchmark and examines whether anomaly detection using machine learning helps to interpret risks from an AML/CFT perspective. This empirical analysis assumes that Elliptic provides an anonymized transaction network in which nodes correspond to Bitcoin transactions, edges reflect directed transactions, and anonymized features facilitate licit/illicit classification of transactions. Furthermore, the dataset is not considered evidence of sender wallet addresses, receiver wallet addresses, transaction amount, timestamp, ownership of exchanges, user geography, and national AML/CFT effectiveness. Based on the labelled analytical dataset presented in the uploaded workbook (46,564 observations, including 42,019 licit transactions and 4,545 illicit transactions), a logit model found a significant positive correlation between illicit transactions and degree centrality (beta = 1.870, p < 0.001), clustering coefficient (beta = 0.940, p < 0.001), and flow entropy (beta = 0.680, p < 0.001). Isolation Forest and Autoencoder reached AUCs of 0.866 and 0.841, respectively. In turn, the coefficient measuring a countryâs regulatory capacity and its interaction term are not included in the estimation because there is no country-window marginal effect. Therefore, this paper does not test for the impact of regulatory capacity of the USA, Singapore, and UAE on transaction classification.
Blockchain and distributed ledger technology (DLT) have been proposed for humanitarian operations because their shared-ledger characteristics may support transparency, traceability, accountability and coordination across organisations. This systematic evidence review synthesises research on operational benefits, adoption barriers, implementation conditions and evidence gaps in humanitarian supply chains. The evidence includes systematic reviews, empirical pilot research, expert-based barrier analysis, case-based design research and implementation-framework studies. Across the literature, the most consistently reported potential benefits are visibility, traceability, transparency, auditability, trust and inter-organisational information sharing. The empirical base is smaller than the conceptual literature, and barriers include regulatory uncertainty, skills and training, sustainability costs, privacy, infrastructure, scalability, interoperability and governance. The review proposes an eight-stage implementation pathway centred on problem diagnosis, technology justification, governance, privacy-aware architecture, piloting, capacity building, evaluation and controlled scaling. The framework is a synthesis proposed by the author from the reviewed evidence, rather than a tested causal model. The review concludes that blockchain should be selected conditionally, where multiple independent actors need a shared auditable record and where the expected coordination value justifies the additional technological and governance complexity.
The rapid digitalisation of healthcare has accelerated the adoption of telemedicine, Electronic Health Records (EHRs), and the Internet of Medical Things (IoMT), transforming healthcare delivery into a highly interconnected and patient-centric ecosystem. In response to growing concerns about data security, privacy, and interoperability, blockchain technology has emerged as a promising solution for its decentralization, immutability, auditability, and secure access control. However, many existing blockchain infrastructures rely on classical cryptographic primitives, including RSA- or elliptic-curve-based public-key mechanisms and cryptographic hash functions such as SHA-256, whose relevant security properties may be affected by sufficiently powerful quantum attacks. This review investigates the convergence of blockchain and quantum technologies to address emerging security threats in e-health systems. A structured literature review was conducted in accordance with the PRISMA 2020 guidelines using the IEEE Xplore, PubMed, ACM Digital Library, Google Scholar, and Crossref databases, covering studies published between January 2018 and June 2025. Following a systematic screening and eligibility-verification process, 57 relevant studies were selected and analyzed. The review evaluates quantum-resilient security mechanisms, including Quantum Key Distribution (QKD), Quantum Random Number Generation (QRNG), and NIST-standardized Post-Quantum Cryptography (PQC) algorithms specified in FIPS 203, FIPS 204, and FIPS 205. Based on the identified research gaps in the state of the art, this study also proposes a novel four-layer Quantum-Blockchain Security Architecture (QBSA) designed for secure healthcare environments. The analysis further reveals significant challenges associated with lightweight PQC deployment for IoMT devices, interoperability standardization, quantum hardware limitations, and regulatory compliance in cross-institutional healthcare systems. The findings highlight the necessity of integrating quantum-resilient cryptographic frameworks with blockchain infrastructures to support the development of secure, scalable, and patient-centric next-generation e-health ecosystems.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
Ida Bagus Mahayana Pidada, Made Aditya Pramana Putra
Blockchain-based smart contracts automate the execution of transactions through computer code, but automation alone does not determine whether the resulting arrangement is a legally binding contract. This article examines the legal status and enforceability of blockchain-based smart contracts as electronic agreements under Indonesian law and evaluates how the validity requirements in Article 1320 of the Indonesian Civil Code operate in a pseudonymous, automated, and relatively immutable technological environment. Using doctrinal legal research, the study integrates the Indonesian Civil Code, the Electronic Information and Transactions Law (EIT Law) as amended by Law No. 1 of 2024, Government Regulation No. 71 of 2019, and current financial-sector regulation, supported by comparative analysis of the UNCITRAL Model Law on Automated Contracting, the UK Law Commission's work on smart legal contracts, and relevant European regulatory design. The analysis finds that Indonesian law can recognize a blockchain-based arrangement as an electronic contract when an identifiable agreement is formed through an electronic system and the substantive validity requirements are satisfied. Government Regulation No. 71 of 2019 is particularly significant because Article 46 reproduces the core elements of contractual validity for electronic contracts, while Article 47 requires party identity, transaction terms, cancellation procedures, and choice-of-law provisions. The principal legal uncertainty therefore lies less in basic contractual validity than in attribution of consent and capacity, code-text inconsistency, automated-agent responsibility, coding or oracle errors, reversibility of remedies, and cross-border enforcement. The article recommends targeted, technology-neutral rules and contractual design safeguards rather than assuming that either code alone or a comprehensive blockchain-specific statute can solve these problems.
Although smart contracts are currently realized in a limited scope around virtual assets, the blockchain characteristics of transparency, immutability, and self-enforcing capabilities hold significant valueâespecially in real estate transactionsâas a way to overcome the limitations of traditional real estate transaction systems, such as double selling and duplicate registration, while improving efficiency. For these reasons, several countries have implemented blockchain technology in their real estate registration or recording systems as well as in smart contracts, and are actively operating them. We also need to identify the pros and cons of these operations and utilize blockchain-based smart contracts for real estate transactions. Under current domestic law, introducing measures to digitize real estate transactions using blockchain technology presents several legal challenges. Key issues include how to address the legal validity of smart contracts, the valuation of tokens, compliance with requirements for the transfer of property rights, the legal effect of public registration, and potential conflicts with data privacy obligations. Therefore, measures to promote smart contracts must be established through a thorough review of their consistency with existing legal frameworks. First, to prepare for the activation of smart contracts, measures to ensure regulatory flexibilityâsuch as standard trading rules that minimize post-contract modificationsâmust be established, along with efforts toward technical standardization. Furthermore, if smart contracts are introduced, attempting to transition the real estate registration system to a blockchain based on its core purpose is the ultimate way to resolve the issues of the existing registration system. Legislative discussion requires establishing legal grounds to grant in rem effect to the digitization and embodiment of real assets, as well as drafting a new registration system to recognize blockchain-based registration records as valid registration for the creation and transfer of real rights. Additionally, relevant legal frameworks must be revised to ensure that the operation of blockchain does not conflict with personal information protection obligations. As blockchain technologyâa core domain of information and communication technology, alongside AIâexpands beyond the socio-economic sphere into daily life, a more advanced discussion is needed regarding the distinct functions or roles smart contracts based on it will play at this current stage.
Purpose This study examines how auditors respond to firms' disclosed blockchain engagement. While the technology offers potential efficiency gains, it also introduces new risks and complexity. We investigate whether and how auditors use audit pricing and auditor resignation as their strategies to manage blockchain-related risks. Design/methodology/approach This study uses a large sample of Chinese A-share listed companies spanning 2016 to 2022. We extract data regarding corporate blockchain engagement by conducting textual analysis on firmsâ publicly disclosed reports. Regression analysis is applied to verify the research hypotheses, followed by a series of robustness tests. In addition, we carry out cross-sectional tests and examine auditorsâ responses to distinct categories of blockchain-related activities. We further investigate the relative priority of auditorsâ risk management strategies and identify potential channels. Findings There is a positive relation between firmsâ disclosed blockchain engagement and audit fees. This relation is more pronounced among larger audit firms, auditors without an information technology (IT) background and those with shorter tenures. Both audit effort and audit risk serve as two plausible channels linking companiesâ engagement in blockchain to increased audit fees. Firms engaging in blockchain to facilitate management processes, rather than provide blockchain-related products or services, are associated with elevated audit fees. Although blockchain engagement is also related to a higher likelihood of auditor resignation, we observe a hierarchical pattern in auditor responses, with fee adjustments being the more prevalent initial reaction relative to resignation. Research limitations/implications Our disclosure-based measure may not fully distinguish the depth of adoption, investor-facing signaling or strategic narrative because doing so would require obtaining in-depth blockchain data from the sample firms. This is highly challenging as such data are not subject to mandatory disclosure by regulators and may constitute corporate confidential information. Our findings should be interpreted as auditorsâ responses to âperceived blockchain-related risksâ rather than a direct response to âthe adoption of blockchain technology.â Practical implications First, for audit firms, our results underscore the importance of investing in technological training and developing firm-level expertise in emerging technologies such as blockchain. The finding that the fee premium is concentrated among auditors without IT backgrounds suggests that audit firms that proactively build technological competence may be better positioned to serve clients engaging with new technologies while managing their own costs. Second, for corporate managers, our findings alert them that public blockchain engagement, even when disclosed for strategic signaling purposes, may carry tangible costs in the form of higher audit fees, particularly when blockchain is deployed for internal management processes. This cost should be factored into firmsâ costâbenefit analyses when making blockchain investment decisions. Third, for regulators and standard-setters, the heterogeneity in auditor responses documented in our study highlights the need for clearer accounting and auditing guidance for blockchain-based transactions, which would reduce the uncertainty that currently drives elevated audit pricing. Originality/value This study provides evidence consistent with auditors strategically adapting to technological disruptions in their risk management practices. The study offers timely and practical insights for auditors, regulators and corporate managers as blockchain applications continue to proliferate.
Marco Scarpa, Mohammad Sadeghzadeh, Saeed Javanmardi, Bahareh Pahlevanzadeh ¡ 5 authors
Blockchain provides secure and decentralized data storage. Normal blockchains permanently store data. Mutable blockchains allow users to change data, but this reduces tamper resistance. This paper tests both methods in PaB-PIF, a hybrid architecture for IoT-Fog networks. Our design uses an immutable mainchain in the cloud layer and mutable sidechains in the fog layer. We analyze throughput, latency, and tamper resistance using math models and simulations. Results show that blockchain greatly improves network security. Without blockchain, the network has zero tamper resistance. The mutable blockchain in the fog layer has a tamper resistance of 0.58. The immutable blockchain in the cloud layer reaches 0.99. However, this extra security increases latency and reduces throughput. The mutable blockchain has lower latency, so it is a good fit for the fog layer. The immutable blockchain provides maximum security, which is best for the cloud layer. This trade-off works well for IoT systems like the Internet of Vehicles, where data integrity and legal rules are essential. We also compare PaB-PIF with an IoT-Fog network that has no blockchain.
The integration of artificial intelligence (AI), the Internet of Things (IoT), and blockchain may provide a viable approach to tackle persistent operational and informational challenges in cleaner production. This conceptual review synthesizes existing literature and presents an integrated AI-IoT-blockchain framework mapped across the four sequential stages of cleaner production: source reduction, process control, end-of-pipe treatment and recycling, and full-chain traceability. The literature indicates that IoT enables real-time sensing, AI drives predictive and prescriptive analytics, and blockchain ensures tamper-proof record-keeping and stakeholder trust. Together, these technologies may help address long-standing barriers including fragmented data, delayed responses, and a lack of verifiability. Despite challenges such as high costs, technical fragmentation, and organizational resistance, several emerging strategies have been proposed in the literature to address these challenges. These include modular deployment, federated learning, permissioned blockchains, and regulatory sandboxes. The frameworkâs underlying architecture appears transferable across sectors, subject to industry-specific adaptation, supporting sustainable manufacturing, the circular economy, and low-carbon development.
Blockchain technology (BCT) is often discussed as digital support for timber traceability in the context of the EU Deforestation-Free Products Regulation (EUDR), which requires operators and traders to demonstrate legality, deforestation-free production, geolocation at the forest parcel level, and verifiable supply chain documentation from 30 December 2026, with an extended timeline for micro, small, and medium-sized enterprises (SMEs) until 30 June 2027. This study assesses where BCT can realistically add value in timber supply chains under operational forestry conditions and identifies the necessary technical, organizational, and legal prerequisites. A combination of a targeted literature review and empirical input from experts in the forestry and timber industry, including guided expert web-conferencing interviews (n = 41), an online survey (n = 69 completed responses), and a transdisciplinary workshop (n = 18) was utilized to obtain a comprehensive overview of industry perspectives. Qualitative data from interviews and workshop sessions were analyzed using structured qualitative content analysis, while survey data were evaluated using descriptive statistics. The expected benefits are associated with the introduction of tamper-proof timber harvesting practices and cross-organizational verification mechanisms. To address the discrepancy between biological uncertainty and digital rigidity, the study proposes a dynamic allocation model adapted from the energy sector that distinguishes between fixed and variable wood capacities to automate logistical planning via smart contracts. However, respondents emphasize that practical obstacles, such as limited digital maturity in forestry, fragmented data infrastructures across the supply chain, and unresolved issues of data sovereignty hinder the implementation of BCT. BCT alone is unable to resolve the problem of weak physical-digital identity continuity, a phenomenon widely known as the oracle problem; however, coupling the ledger with physical or biological anchors (e.g., photo-optical, automated inkjet marking identification) can re-establish this physicalâdigital continuity and thereby resolve the oracle problem. The results demonstrate that blockchain acts most plausibly as a supporting component within hybrid traceability architectures that prioritize event-based authentication, off-chain data processing where appropriate, and integration with existing certification systems. The study highlights the necessity of defining distinct organizational roles and responsibilities while integrating user-centric digital solutions tailored specifically to small and medium-sized enterprises (SMEs).
Modern charitable donation platforms involve multiple stakeholders, including donors, charity organizations, financial institutions, and regulatory authorities. However, traditional centralized systems often suffer from limited transparency, weak trust management, and insufficient traceability, which significantly undermine public confidence in charitable activities. To address these challenges, this study proposes an intelligent blockchain-enabled framework for transparent multi-stakeholder donation management. The proposed system integrates consortium blockchain infrastructure with smart contract mechanisms to support trustworthy transactions, automated governance, and transparent information sharing across participating entities. The framework adopts a modular architecture that facilitates role separation, traceable transaction management, and scalable system evolution. In addition, the system enables transparent supervision and evaluation processes, allowing donors, recipients, and regulatory bodies to participate in collaborative monitoring of charitable activities. A prototype implementation based on the FISCO BCOS consortium blockchain platform is developed to evaluate the feasibility and performance of the proposed framework. Experimental results demonstrate that the system effectively enhances traceability, operational transparency, and trust among participants while maintaining acceptable performance in terms of throughput and latency. The proposed framework provides a practical reference architecture for developing intelligent and trustworthy multi-party platforms and contributes new insights into the design of decentralized expert systems for social good applications.
The increasing digitalization of higher education has created growing demands for secure and transparent academic data management. As a background, conventional academic information systems remain vulnerable to data manipulation, unauthorized access, and difficulties in verifying the authenticity of academic records. Therefore, the objective of this study is to investigate the role of blockchain technology in enhancing academic data security and transparency within higher education institutions. The method employed in this research is a quantitative approach using a survey questionnaire distributed to 173 respondents consisting of students, academic staff, and administrative personnel from various higher education institutions. The collected data were analyzed using Structural Equation Modeling (SEM) to examine the relationships between blockchain technology adoption, academic data security, and academic transparency. The results reveal that blockchain technology has a significant positive effect on academic data security by providing decentralized data storage, cryptographic protection, and immutable transaction records. In addition, blockchain implementation significantly improves academic transparency by enabling reliable verification, traceability, and authenticity of academic information and credentials. The findings suggest that blockchain technology can minimize the risk of data tampering while strengthening stakeholder trust in academic information systems. In conclusion, blockchain technology serves as an effective solution for improving academic data security and transparency, contributing to the development of a trustworthy and data-driven governance framework in higher education institutions.
The study aimed to investigate the perceived application of Blockchain technology among accountants, auditors, bankers, and other related professionals in Iraq and the statistical association between this perceived application and financial-information reliability, based on respondentsâ perceptions of financial-information reliability. The study was designed as a field study using a five-point Likert scale. The analysis was based on 150 valid responses. Blockchain application was measured using ten items, and financial information reliability was measured using another ten items. Cronbach's alpha coefficient, descriptive statistics, Pearson and Spearman correlation coefficients, and simple linear regression were used. The results of the Blockchain scale showed acceptable internal consistency (Îą = 0.775), while the financial information reliability scale showed very high internal consistency (Îą = 0.989). The mean scores were 4.232 and 4.221, respectively. Pearson's correlation coefficient was positive but not statistically significant (r = 0.146, p = 0.076), and the regression model was also not statistically significant (R² = 0.021, F(1, 148) = 3.203, p = 0.076). The results indicate positive perceptions of Blockchain technology and the reliability of financial information. However, the current data do not provide sufficient evidence at the 5% significance level that perceived Blockchain application is statistically significantly associated with financial-information reliability.
Satyam Prakash Srivastava, Rupa Khanna Malhotra, Priyanshu Sagar
The blockchain technology in the banking sector is a decentralized ledger system and has been more commonly known by it being the basis of cryptocurrencies, such as Bitcoin. However, blockchain is to Bitcoin, as email is to internet; the possible areas of examination with the use of blockchain technology are gigantic. One of such areas is the banking sector, which has certain ambiguities, which needs to be spoken about proximately, such as the lack of distinct accountability, disorganization in deliverance on time, deficiency of transparency, and âtoo big to operate effectivelyâ kind of attitude. This research work is based on the careful exploration, examination, and evaluation of the possible methods of applying blockchain technology in the banking sector.