Recording entry and exit records for a country, with properties such as confidentiality, integrity, and auditability, is increasingly important due to rising international mobility and security requirements. Traditional border control systems, which rely on centralised databases, are vulnerable to data manipulation and have limited interoperability between institutions. This study presents GateChain, a blockchain-based application that addresses these vulnerabilities. GateChain aims to enhance data integrity, reliability, and transparency by recording entry and exit events on a distributed, immutable, and cryptographically verifiable ledger. The application provides real-time access control and verification for authorised institutions. This paper describes the architecture and security components of GateChain and evaluates its performance and security features.
Bitcoin derives a verifiable temporal order from probabilistic block discovery and cumulative proof-of-work rather than from a trusted global clock. We show that block arrivals exhibit stable exponential behavior across difficulty epochs, and that the proof-of-work process maintains a high-entropy search state that collapses discretely upon the discovery of a valid block. This entropy-based interpretation provides a mechanistic account of Bitcoin's non-continuous temporal structure. In a distributed network, however, entropy collapse is not completed instantaneously across all participants. Using empirical observations of temporary forks, we show that collapse completion unfolds over a finite propagation-bounded interval, while remaining rapid in practice.
Bitcoinâs price dynamics are influenced by both internal factors (e.g., supply shocks, investor sentiment) and external drivers, among which the stability of stablecoins has attracted increasing academic and regulatory attention. This paper investigates the effect of stablecoin peg deviations (USDT and USDC) on Bitcoin returns using daily data from January 2020 to August 2025. Based on a vector autoregression (VAR) framework, we conduct unit root tests, lag order selection, model estimation, Granger causality tests, and impulse response analysis. Results show that both Bitcoin returns and stablecoin deviations exhibit strong short-term inertia. USDT and USDC deviations significantly Granger-cause Bitcoin returns, whereas the reverse causality is weaker. Impulse responses indicate that stablecoin deviations first produce positive shocks to Bitcoin returns, followed by negative corrections that gradually stabilize. The effect of USDT is more pronounced and persistent, underscoring its central role in cryptocurrency markets. These findings highlight the importance of monitoring stablecoin market stability, especially USDT, for investors and regulators seeking to manage systemic risks in crypto markets.
This article develops a methodological approach to the digital transformation of public administration for sports infrastructure at the regional level under the systemic challenges of martial law. The relevance of this research is determined by the necessity to transition from universal digitalisation models to targeted technological solutions capable of addressing specific institutional dysfunctions within the management system. The aim of this article is to substantiate the methodology of targeted digitalisation as an alternative to comprehensive automation of management processes in the sphere of sports infrastructure. The research combines empirical analysis of management practices with theoretical modelling of digital transformation mechanisms, employing the concept of âdigital leversâ for organisational change adapted from Westerman, Bonnet, and McAfeeâs framework.The study identifies systemic dysfunctions in public administration, including fragmentation of the management hierarchy, deficiency of control mechanisms, limited regional absorptive capacity, and institutional barriers to innovation implementation. Through triangulation of budgetary reporting data, audit conclusions from the Accounting Chamber of Ukraine, and technical documentation from the DREAM digital platform, the research reveals a fundamental disconnect between technological capabilities and institutional readiness for transformation. The developed targeted digitalisation matrix establishes a methodological connection between the characteristics of management pathologies and the functional capabilities of digital technologies. This approach differentiates technological interventions according to three criteria: the nature of dysfunction (structural, procedural, behavioural), the level of digital maturity amongst management entities, and existing resource constraints.The principle of âproblem-oriented digitalisationâ is substantiated, whereby technologies are selected not for their innovative qualities but for their capacity to influence the reproduction mechanisms of specific management dysfunctions. Each digital instrument is mapped to particular pathology reproduction mechanisms: automation reduces subjective factor influence, distributed ledger technology ensures data immutability, machine learning algorithms optimise resource allocation, and IoT networks provide objective infrastructure monitoring. The research demonstrates that whilst platform-based solutions like DREAM represent technological advancement, their effectiveness remains limited without addressing underlying institutional incentives that perpetuate dysfunctional practices.Prospects for implementing distributed ledger technologies are identified for ensuring transparency of financial flows and automating resource allocation through smart contracts. The study proposes a three-tier implementation architecture: cloud-based solutions for frontline territories lacking local infrastructure, hybrid platforms for regions with moderate capacity, and comprehensive smart ecosystems for developed urban centres. The conclusion is drawn that targeted digitalisation ensures systemic transformation of public administration through precise impact on the reproduction mechanisms of institutional pathologies, unlike universal solutions that merely digitise existing inefficient practices. This methodological approach offers particular value for post-conflict reconstruction contexts where resource constraints demand maximum efficiency in technological investments.
As stablecoins become increasingly prevalent in financial crimes, their usage for illicit activities has reached a scale of USD 51.3 billion. Detecting phishing activities within stablecoin transactions has emerged as a critical challenge in blockchain security. Currently, existing detection methods predominantly target mainstream cryptocurrencies like Ethereum and lack specialized models tailored to the unique transaction patterns of stablecoin networks. This paper introduces a deep learning framework, BERTSC, based on multi-modal fusion. The model integrates three core modules graph convolutional networks (GCNs), BERT semantic encoders, and soft prompt encoders to identify malicious accounts. The GCN constructs directed multi-graph representations of account interactions, incorporating multi-dimensional edge features; the BERT encoder transforms discrete transaction attributes into semantically rich continuous vector representations; the soft prompt encoder maps account interaction features into learnable prompt vectors. An innovative three-way gated dynamic fusion mechanism optimally combines the information from these sources. The fused features are then classified to predict phishing account labels, facilitating the detection of phishing scams in stablecoin transaction datasets. Experimental results on large-scale stablecoin datasets demonstrate that BERTSC outperforms baseline models, achieving improvements of 4.96%, 3.60%, and 4.23% in Precision, Recall, and F1-score, respectively. Ablation studies validate the effectiveness of each module and confirm the necessity and superiority of the three-way gating fusion mechanism. This research offers a novel technical approach for phishing detection within blockchain stablecoin ecosystems.
Spa services in wellness tourism often face limitations in transparency, service integration, and customer trust in operational flows. This study develops a blockchain-based smart contract model that integrates five key indicators: reservations, cancellations, customer satisfaction, inventory, scheduling, and finance. A literature review of 113 articles yielded 25 key references, with significant trends such as the occurrence of the keyword âcustomer reservationâ 10,100 times (2020â2024). Linear regression, correlation analysis, and ANOVA methods were used to test the research results. Linear regression predicts the relationship between variables, while correlation measures the strength of the relationship. The calculation results show a Pearson correlation coefficient of 0.93 (α = 0.05), indicating a very strong linear relationship. ANOVA shows significant differences between groups. These findings confirm that blockchain-based smart contracts are effective in digitally automating spa service workflows, strengthening transparency, and improving customer satisfaction
Dr. Megala Rajendran, R. Gopalakrishnan, Dr.A. Dharmaraj, Dadajon Dadabayev Rustamovich
Background: Quantum computing poses a threat to classical signatures, like ECDSA, and makes long-lived blockchain smart contracts, particularly those used in a system of the circular economy and sustainability, susceptible to future forgery and governance attacks. Abstract: This paper presents a quantum resilient smart contract lattice architecture to achieve ethical governance and resource tracking in the use of a circular economy and maintain realistic performance. Methods: The architecture uses a NISTâtrack latticeâbased postâquantum signature scheme (CRYSTALSâDilithium) with one signature per transaction in an Ethereumâlike environment, adds batched postâquantum verification opcodes to the virtual machine and a postâquantumâaware gas model, and introduces Solidity contracts for recycle passports, tokenized wasteâmanagement incentives, and DAOâbased governance. Ethical governance is operationalized using a transparency index together with quantitative fairness and inclusiveness measures derived from reward distributions and participation rates. Results: The proposed framework has a 2.0 ms verification latency, 450 transactions per block, 70% relative throughput, and 130 GB/year storage, compared to 2.8 ms verification, 268 transactions per block, 55% relative throughput, and 140 GB/year storage in the hybrid postâquantum baseline and the classical ECDSA configuration. Conclusion: These findings suggest quantum resilient smart contracts are a promising basis of long-horizon circular economy governance, which provides superior security and ethics by design assurances and sustains competitive performance and sustainability attributes compared to both classical and hybrid post-quantum baselines.
This comprehensive technical survey presents integration architectures for the Y.I.N. (Your Information Never leaves your control) Nine Pillars framework across 200+ commercial platforms spanning artificial intelligence (100+ LLM providers including OpenAI, Anthropic, Google DeepMind, Meta, Microsoft, Mistral AI, Baidu, Alibaba, Tencent), healthcare (50+ providers including Epic Systems, Tempus, PathAI), finance (40+ institutions including JPMorgan Chase, Goldman Sachs, BlackRock), autonomous vehicles (20+ companies including Waymo, Tesla, Cruise), telecommunications (25+ carriers including AT&T, China Mobile, Deutsche Telekom), and energy (20+ companies including Siemens Energy, NextEra) across 25+ countries. The Y.I.N. Nine Pillars architecture provides end-to-end privacy protection through: (1) Data Privacy (Differential Privacy), (2) Computation Privacy (Homomorphic Encryption), (3) Storage Privacy (Encryption at Rest), (4) Transmission Privacy (TLS 1.3), (5) Access Control (Zero-Knowledge Proofs), (6) Audit Trail (Merkle Trees), (7) Deletion Rights (Cryptographic Erasure), (8) Quantum Resistance (Lattice-based Cryptography), and (9) Token Licensing (Cryptographic Payment Enforcement). The Ninth Pillar token licensing system, covered by U.S. Patent Application 63/949,361 (filed December 28, 2025), provides cryptographic enforcement of usage rights by integrating token-derived blinding factors into homomorphic encryption operations, making computational correctness mathematically dependent on valid authorization. The system achieves 99.37% accuracy with valid tokens versus 50.7% with invalid tokens (t=147.3, p<10^-50), with security proven under CDH hardness (2^128 operations) and Ring-LWE assumptions. Integration schematics are provided for regulatory compliance with HIPAA (healthcare), SOX/DORA (finance), GDPR/EU AI Act (European Union), CCPA (California), PIPL (China), ISO 27001, NERC CIP (energy), and 15+ other frameworks. Extension directions are documented for community research including TEE hybrid architectures, MPC integration, VDF token lifetimes, key-homomorphic PRFs, flexible validation policies, hardware attestation, ABE capabilities, off-chain settlement, and DID/VC integration. Organizations seeking to implement these integration patterns may obtain licenses for individual pillars, sector packages, or the complete Nine Pillars system from the patent holder. Patent Notice: The Y.I.N. Nine Pillars architecture and Ninth Pillar token licensing system are covered by U.S. Patent Applications 63/949,361 (Ninth Pillar, filed December 28, 2025), 63/923,348 (QFED-MAZARI Quantum Extensions), 19/399,646 (Core Y.I.N. Architecture), 19/403,244 (Hardware Implementation), and 19/417,196 (SQL Database Integration), comprising 430+ claims across 15 patent applications.
L. B. WANG, Liming Zhang, Ruitao Qu, Tao Tan · 6 authors
Existing vector geographic data transaction schemes are typically merchant-controlled, hindering fair ownership tracing and impartial arbitration. To address this, we propose an asymmetric digital fingerprinting scheme based on smart contracts. In our approach, the user encrypts a proof fingerprint with a public key and sends it to the merchant; the merchant leverages the additive homomorphic property of the Paillier cryptosystem to embed the encrypted user fingerprint into an encrypted portion of the vector data while embedding a tracking fingerprint into the plaintext portion. The combined data is delivered to the user, who uses their private key to decrypt the encrypted part and obtain the plaintext data containing both fingerprints. This design enables tracing of unauthorized distribution without exposing the userâs fingerprint in plaintext, preventing malicious accusations. By leveraging blockchain immutability and smart contract automation, the scheme supports secure, transparent transactions and decentralized arbitration without third-party involvement, thereby reducing collusion risk and protecting both partiesâ rights.
Open access
Advanced Steganography and Watermarking Techniques
Communication and information technologies have facilitated the rapid adoption of electronic medical records, leading to patient privacy and data security concerns. Blockchain technology offers a promising solution to address these issues. However, scalability remains a significant challenge for blockchain-based electronic health records (EHR) systems. In this study, we aimed to develop and evaluate an EHR management system based on blockchain technology. Therefore, we propose a management model based on organizations and user roles and implemented it using Hyperledger Fabric and the InterPlanetary File System (IPFS). The blockchain consists of three channels: one for patient registration and EHR retrieval and two additional channels dedicated to two hospitals for storing patientsâ EHRs. A scalable multichain e-health system using the Hyperledger Fabric platform provides a practical option to address scalability issues and protect patientsâ privacy, security, and medical data. The proposed model uses IPFS to store medical images and generate hash values, which are then stored in the blockchain. The system was evaluated using Hyperledger Explorer and Hyperledger Caliper, focusing on several performance metrics: transactions per hour, transactions per minute, blocks per hour, blocks per minute, response time, maximum latency, minimum latency, average latency, throughput, CPU and memory usage, and runtime. A comparative analysis was conducted against single-ledger EHR systems to assess the proposed systemâs performance. The Hyperledger Caliper report shows that the average latency for each organization ranges from 0.11 to 0.55, and the throughput ranges from 24.2 to 200 for 1000 assets at sending rates of 25, 50, 100, and 200.
This paper presents a QMU-native extension of electrodynamics that reconstructs the auxiliary fields $(D,H)$ as a constitutive layer over a geometry-first Maxwell ledger. The central objective is to retain the classical operational split between $(E,B)$ and $(D,H)$ while enforcing QMU semantics: (i) dual charge channels (electrostatic vs magnetic), (ii) explicit singular-to-distributed charge conversion rules with a defined exception class, and (iii) a two-layer field dictionary that cleanly separates flux-density variables from strength variables. \medskipThe vacuum sector is closed by geometric identities rather than empirical medium constants, including the speed closure $c=\lambda_C F_q$, the channel conversion $e^2/{e_\mathrm{emax}}^{2}=8\pi\alpha$, and a seat-map normalization expressed through $A_u/k_C=16\pi^{2}$. Within this framework, permeability and permittivity are treated as QMU substrate ratios,\[\mathrm{perm}=\frac{1}{\mathrm{curl}},\qquad \mathrm{ptty}=\frac{1}{A_u},\]so that the propagation scale factorizes exactly as\[\mathrm{perm}\,\mathrm{ptty}=\frac{1}{c^2}.\]This yields a wave operator that is naturally expressed in terms of the torsion--rotation product. \medskipA two-layer dictionary is introduced in which $(D,B)$ represent flux-density fields and $(E,H)$ represent operational strength fields, connected in uniform Aether by a geometric lift proportional to the quantum length. Independently, the paper defines constitutive-conjugate strengths $(E^{\star},H^{\star})$ that pair directly with the exception-class response operators in boundary-value and material problems. The two strength notions are reconciled algebraically in isotropic vacuum, clarifying how QMU separates local forcing scales from substrate response scales. \medskipFor non-uniform rotating-magnetic-field (rmfd) states, the constitutive law is promoted to a linear operator deformation driven by the rmfd non-uniformity tensor $\Theta_{ij}=\nabla_i U_j$ with dimensionless couplings $(\chi_E,\chi_H)$. In the local plane-wave limit, this produces a first-order polarization eigenproblem whose birefringent splitting is governed by the transverse symmetric strain and the combined coupling $(\chi_E+\chi_H)$. The paper provides compact invariants for the transverse shear sector and an interferometric path-integrated phase observable suitable for QMU-only laboratory discriminators. \medskipAn appendix provides a conventional-constant crosswalk as a reader-facing translation layer only; it is not used in the QMU constitutive derivations.
This article examines the legal status of smart contracts across different jurisdictions through a comparative legal methodology, analyzing regulatory approaches in the United States, European Union, Switzerland, Singapore, and Uzbekistan. The research identifies key challenges in integrating self-executing agreements into existing legal frameworks, including issues of contract formation, enforceability, dispute resolution, and data protection compliance. Using doctrinal analysis and comparative law methods, this study evaluates how different legal systems address the fundamental question of whether code-based agreements satisfy traditional contract formation requirements. The findings reveal a spectrum of regulatory responses ranging from explicit statutory recognition to application of existing contract law principles. The article concludes with recommendations for developing comprehensive legal frameworks that balance innovation with consumer protection and legal certainty.
The state-of-the-art review comprehensively examines access control mechanisms for securing cloud computing environments, emphasizing their architectural evolution and performance efficiency. Conventional access control models such as Role Based Access Control (RBAC) and Attribute Based Encryption (ABE), though widely adopted, continue to face limitations including single points of failure, centralized policy management, and limited transparency in audit trails. Recent studies report average encryption and decryption times below one second in conventional schemes, yet these models struggle with scalability and dynamic revocation in distributed settings. The integration of blockchain technology addresses many of these challenges through its decentralized, immutable, and transparent infrastructure. Blockchain based access control frameworks implemented on platforms such as Hyperledger Fabric and Ethereum leverage smart contracts to automate policy enforcement and achieve throughput gains of up to 42 percent with transaction latencies near 39 milliseconds. By distributing trust and enabling verifiable audit trails, these models enhance data integrity, accountability, and compliance. This survey consolidates and analyzes current research in both conventional and blockchain based access control for cloud and IoT ecosystems, identifying performance tradeoffs, regulatory considerations, and future research directions toward secure, transparent, and scalable access management.
The global expansion of Bitcoin and cryptocurrencies brings unanswered questions of the Islamic finance that are legal in nature. The existing research is divided into two camps, namely, total prohibition, or conditional acceptance. It is a thematic analysis of 32 public fatwas (2014-2024) of 12 Islamic jurisdictions in the first systematic analysis. The application of cryptocurrencies and their Shariah acceptability are analyzed. This paper applies the six-stage model offered by Braun and Clarke and it establishes five key jurist themes. The former theme is the ambiguity of the issue of whether cryptocurrencies are to be treated as mal (property) or thamaniyyah (money). The second theme talks about gharar, i.e., excessive uncertainty that is caused by volatility, lack of transparency and regulatory instability. The third theme concerns speculation by trading which is similar to maysir (gambling). The fourth theme is about mafsadah, which is harm to society and includes illicit use, environmental costs and inequality. Lastly, the fifth theme is on interpretations and deviations which form conditional permissibility in the presence of regulation and transparency, which minimises the risks of jurisprudence. The findings indicate that juristic disagreement is not an issue of inconsistency but the use of the various kinds of reasoning on novel financial technologies. The study paves the way in the study of Islamic-finance, by transforming the disjointed textual load of fatwa into a juristic map, which articulates the reasons behind the variance of rulings, as opposed to how they vary. This paper can be used by Shariah boards, regulators, and developers of digital assets to take action on implementing maqasid al-Shari, in the regulation of digital assets.
This thesis investigates the design of automated market makers (AMMs) for trading tokenized derivatives in decentralized finance. Motivated by the limitations of existing AMMs, which only permit strictly positive prices, we introduce an invariant that also allows for negative prices. As a primary use case, the thesis develops an AMM for trading an offset token against tokenized euros. The thesis employs, on the one hand, a Monte Carloâbased simulation to evaluate the risk-adjusted returns of an AMM. The simulation includes two types of traders: arbitrage traders, who exploit price deviations between the AMM and the fair value, and noise traders, who represent demand for liquidity. On the other hand, we introduce KPIs such as impermanent loss and market depth. The goal of the thesis is to analyse whether these KPIs can be used to predict the risk-adjusted returns of an AMM.
Purpose We investigate the presence of contagion between Bitcoin and four traditional assets (stocks, bonds, gold and the US dollar exchange rate) over the period 2015â2024. Design/methodology/approach We implement a framework that combines the DCC-GARCH specification and a time-varying causal inference methodology. Findings Our findings support that Bitcoin remains weakly connected to the global financial markets. Contagion is limited, appearing sporadically from S&P 500 to Bitcoin and from Bitcoin to the US dollar index. However, when we impose a stricter definition of extreme correlation or a multivariate VAR specification, the contagion results vanish, indicating no systematic contagion between Bitcoin and traditional assets. Practical implications Our evidence implies that Bitcoin may be used as a useful portfolio diversification instrument. Originality/value We deploy a recently developed novel methodology that combines the DCC-GARCH model and a recent time-varying Granger causality procedure to distinguish between extreme high correlation and contagion and find no evidence of systematic contagion effects of Bitcoin with conventional asset classes.
First-order science lacks enforced closure on the objects it manipulates (hypotheses, methods, results, interpretations). This produces predictable failure modes: bounded message one-shot evaluation cannot reliably accept framework-extending claims; operational coherence degrades as unresolved constraints accumulate; and distributed evidence for universality claims is repeatedly reset by demands for single decisive tests. These failures are structural, not contingent, and cannot be repaired by incremental reforms internal to first-order process norms.[T] Necessity result (reverse approach): We prove that any process that restores coherence under unbounded novelty must implement an adaptive functional core isomorphic (up to representation) to a canonical operator algebra. Consequently, any cross-domain coherence solution must factor as domain-relative external operators plus a domain-invariant internal core of the FMA form. The Functional Model of Adaptation (FMA) is treated as a canonical representative of this necessity class, not as a speculative content model to be âproven trueâ under first-order standards.[E] Second-order instantiation: We define a strongly typed evidence ledger with explicit accumulation operators, persistence rules, and threshold conditions. The paper is not an argument for second-order science; it instantiates second-order science. Evaluate it by the ledger and its admissible moves.
Financial reporting within enterprise resource planning now commonly rides on a blockchain backbone, yet the problem of keeping each distributed ledger in sync remains stubbornly difficult-especially when SAP modules are at the controls. This paper describes a simulation-based testbed that watches SAP payment journals as they hop between differently configured blockchains, measuring how and when each copy reaches the same state. By replaying typical SAP routines under adjustable delay windows and choice of consensus rules, the model tallies the frequency of divergence, the lag before agreement, and the mechanics of clearing up disputes. Output files display convex 3D surfaces, animated heat maps, and step-by-step trails of how conflicts get settled; taken together, they point middleware designers toward tighter sync logic, smarter contract frameworks, and faster multi-ledger audits. In broader terms, the findings shrink the technical distance SAP users must traverse to achieve clean, traceable cross-chain accounting.
Smart contracts, self-executing protocols on blockchain platforms, challenge traditional contract law by automating performance without intermediaries. This doctrinal study examines their enforceability under Indian statutes, particularly the Indian Contract Act, 1872, and the Information Technology Act, 2000. The research problem centres on whether code-based agreements satisfy essential elements like offer, acceptance, free consent, and lawful consideration, amid ambiguities in evidentiary admissibility and remedies. Objectives include analysing statutory compatibility, identifying doctrinal gaps, and proposing reforms. Through examination of sections 10, 13-14, and 10A of relevant Acts, alongside judicial precedents on electronic contracts, findings reveal partial recognition: smart contracts qualify as valid if hybrid (code plus natural language) and digitally signed, but pure code versions face hurdles in proving intent and consent. Key challenges encompass immutability conflicting with revocation rights and cross-border jurisdiction issues. The study recommends legislative amendments for explicit recognition, judicial guidelines for code interpretation, and regulatory sandboxes. Ultimately, smart contracts hold transformative potential for India's digital economy if integrated via interpretive evolution and targeted reforms, balancing innovation with legal certainty.
Marwa Ali Hamdan AL-Jabri, Nafisa Abul Ghafoor Othman AL-Ansari
Access control is an important part of cybersecurity in distributed systems since conventional centralized mechanisms are not always sufficient. Due to blockchain, individuals have begun to employ decentralized access control models as they are capable of enhancing transparency, auditing and defending against fraud. At the reason of this report, we survey various blockchain-based access control systems, paying special attention to their architectures, confirmation mechanisms, identity models and policy enforcement mechanisms. We categorize the current literature into various groups based on their platforms (e.g. Ethereum, Hyperledger, Fabric), control mechanisms (e.g. RBAC, ABAC and capability-based) and whether they introduce additional privacy-tools such as zero-knowledge proofs and decentralized identifiers. The paper analyzes and describes the key gaps in current frameworks in terms of scalability, interoperability and computing expenses. Then, the shortcomings of the current research are pointed out so that they could guide future efforts in the field of blockchain-based access control systems.
This study investigates the relationship between dirty and clean cryptocurrencies and traditional stock index returns using the Quantile-Quantile (QQR) and Quantile-Quantile Granger Causality (QQGC) methods. The analyses were conducted using daily data from January 2018 to May 2025. QQR results show both positive and negative relationships between dirty and clean cryptocurrencies and the returns of the S&P 500, FTSE 100, TSX, and ASX indices at the low, medium, and high quantiles. According to the QQGC results, both dirty and clean cryptocurrencies showed predictive power for the returns of the S&P 500, FTSE 100, TSX, and ASX indices at different quantiles. Furthermore, it was found that both dirty and clean cryptocurrencies exhibit strong predictive power for S&P 500 and FTSE 100 returns, particularly in the middle quantiles. The results obtained reveal that distinguishing between dirty and clean cryptocurrencies under different market conditions provides important insights for investors' portfolio diversification strategies and risk management practices.
Drawing on feminist scholarship on money and finance and Âgeographical scholarship on everyday life and masculinities, this article examines the promises and futures that investment in and use of cryptocurrency represents for men in the UK. We explore the financial practices, logics and decision-making of ordinary crypto-users and examine how engagement with cryptocurrency shapes how these men understand themselves, their futures, and their place in the broader world. Through focus group and interview data we explore how research participants explain their rationale and motivations for their financial practices, including examining menâs perceptions of and relations to cryptocurrency, and how these shape and are shaped by the intimacies and moralities of everyday life. Based on our findings, we conceptualise crypto-masculinities as a historically and socially specific financial practice and gendered expression of the relations of (digital) money and finance. This article remedies the limited geographical attention that has been paid thus far to cryptocurrency âusersâ, and offers novel insights into the embodied dimensions of cryptocurrency use, including how cryptocurrency is experienced and lived.
Investigations of cybercrime today require forensic architectures that natively traverse multiple blockchains with ease while protecting and scaling evidence processing. Although blockchains support tamper- evident logs, their original single-chain architecture limits cross-platform interoperability and forensic scaling. Recent developments overcome these limitations such as zero-knowledge proofs supporting private but verifiable evidence verification, sharding architectures splitting state without compromising latency, and AI-based anomaly detectors identifying subtle tampering. But challenges remains like zero- knowledge proofs are computationally expensive, sharding poses intricate state-consistency problems and AI models need to be retrained constantly, incurring operational burden. Future research needs to make these pieces work for real- time, large-scale forensic applications by designing light-weight zero-knowledge constructs, self-tuning shard governance systems and compact AI with incremental-update threads. Integrating such abilities into single frameworks will offer privacy, scalability and security, supporting forensic processes for which courts will give credit in various, changing block-chain environments.