The dissertation examines statistical arbitrage methods in the cryptocurrency markets using cointegration analysis on Bitcoin, ethereum, Litecoin, Ripple using daily price data of the cryptocurrencies between January 2022 and October 2024. The research deploys strict econometric procedures, such as the Engle-Granger two-step process and Johansen test, to uncover and take advantage of the mean-reverting relationships between the key cryptocurrencies. Findings indicate that there are strong relationships of cointegration especially between Bitcoin-Ether and Ethereum-Litecoin with the relationship between Bitcoin-Ether and Ethereum being very stable in many market regimes. The statistically arbitrage strategies depending on such cointegrated pairs led to large risk-adjusted returns whose Sharpe ratios of 1.58 to 2.45 were markedly higher than buy-and-hold standards. The Bitcoin-Etherer pairs trading strategy had an annualized return of 16.34 evidenced by a volatility of just 8.45 against the volatility of Bitcoin on buy and hold at 54.67. These strategies had low beta (0.09-0.18), which was an affirmative of their market-neutral qualities and their positive alpha generation of between 11-15% per annum.
This paper formalizes a mathematical physics framework for redefining the “charge” entity within physical plasma settings using the Hala-SCC (Successive Controlled Collapse) protocol. Traditionally viewed as a static dipole, we re-model charge as a dynamic informational inheritance that manifests in three distinct physical phases: Discrete (species), Wave (EM fields), and Continuum (current flow). By integrating fuzzy logic with the Hala Operator ( ˆH), we introduce the concept of Gray Entropy—a stabilized transitional state that prevents “topological tearing” during the transition from high-entropy chaotic inheritance to zero-entropy epistemological truth. Through a 23 factorial Design of Experiments (DoE) conducted on a quiescent multi-dipole thermionic plasma source, we demonstrate that the synergy between Human, Artificial, and Protocol intelligence operators allows for a “Managed Viscosity” of knowledge. This framework provides the first deterministic proof that the “charge” carrier can be distilled into a stable industrial logic gate, bridging the Reality Gap (ϵ) between abstract plasma theory and engineering utility.
Disha Pardeshi, Sujata Sathe, Viha Bakshi, Ananya Mary Sebastian
AbstractThe growing need for secure and transparent electoral systems highlights the challenges faced by Non-Resident Indian (NRI) voters. Current rules requiring physical presence at polling stations limit participation, despite rising registrations. In our proposed blockchain-based voting framework, votes are transmitted through a secure virtual private network (VPN) and authenticated at the Election Commission of India (ECI) gateway node. After authentication, the votes are verified across multiple blockchain nodes using a consensus mechanism. Once validation is completed, the votes are permanently recorded in the distributed ledger, ensuring that they cannot be altered or removed. Smart contracts are employed to automate the vote-counting process, reducing manual intervention and minimizing the possibility of human error. The final election results are then made available through the ECI dashboard, enabling transparency and easy verification by authorized stakeholders.The proposed framework aims to improve accessibility for Non-Resident Indian (NRI) voters by enabling secure remote participation while preserving voter anonymity. By strengthening trust in the electoral system and encouraging wider participation, the solution supports improved electoral integrity. Overall, the integration of blockchain technology into the voting process contributes toward building a more transparent, secure, and inclusive democratic system in India.Keywords: Blockchain, NRI Voting, Distributed Ledger, Electoral Integrity, Consensus Mechanism, Immutability, Voter Anonymity.
Within the context of digital forensics, the integrity and authenticity of digital evidence are crucial for its legal admissibility within a courtroom setting. Chain of Custody (CoC) processes ensure that digital evidence is meticulously managed and documented from its point of origin until its use in legal proceedings. As the importance of digital forensics increases, especially with cybercrime investigations, the traditional processes used in traditional Chain of Custody have challenges in terms of transparency, security, and efficiency. This paper highlights some of the recent developments in Chain of Custody processes, particularly with the adoption of blockchain and Artificial Intelligence technologies. Blockchain technology, known for its impenetrable and distributed properties, introduces a new paradigm for Chain of Custody processes, enhancing security and traceability for digital evidence management. Additionally, AI-based algorithms for anomaly detection have the potential for increasing the reliability of Chain of Custody processes. Moreover, we will explore the decentralized evidence storage approaches and privacy-preserving mechanisms, such as zero-knowledge proofs. These are important in ensuring that more secure yet transparent approaches in managing distributed forensic investigation systems are achieved. The effectiveness of currently used CoC approaches presents lessons in understanding the future of improving the integrity of this process. Such innovations have the potential of revolutionizing the field of digital forensic investigation processes while ensuring that the handling of such evidence is of the highest integrity.
Yescha Nuradisa Ekarachmi Danandjojo, Samira Ramezani, Johan Woltjer, Taede Tillema
• Policies both enable and constrain LVC, requiring flexible regulatory alignment. • Limited local fiscal authority weakens LVC use for transport infrastructure funding. • MRT Jakarta shows transit agencies need clear mandates and institutional support. • Intergovernmental collaboration is essential for effective LVC in multi-level systems. • Effective LVC needs risk sharing, incentives, and non-fiscal tools for private actors. Discussions of stakeholder relationships in land value capture (LVC) for transport infrastructure development remain limited, particularly within decentralized systems in the Global South and in multi-level government contexts, where strong government control is present. This paper examines the factors affecting stakeholder relationships and how these relationships influence the implementation of LVC. The case study focuses on Jakarta’s Mass Rapid Transit (MRT) in Indonesia, where LVC is considered a promising financing tool. The findings highlight that in the context of Jakarta, policy and regulations, institutional arrangements, and risk mitigation are the most influential factors. First, while policies and regulations are essential in defining stakeholder responsibilities, they also create rigid boundaries that can limit flexibility for local innovation in exploring LVC instruments. Second, the limited authority of the transit agency indicates the need for more explicit mandates and greater support from governing bodies. Third, public agencies need to take a more proactive role in risk mitigation by developing mutually beneficial partnerships with private entities. Overall, this study bridges theory and practice by placing LVC within a multi-level governance framework that links the governance of transport infrastructure development and land-use management. It shows that successful LVC implementation depends on collaboration among stakeholders from different sectors and requires institutional flexibility and adaptive governance that balance national policy coherence with local discretion. By highlighting these cross-sector and governance dynamics, the study contributes to wider discussions on urban development, transport infrastructure governance, and public–private collaboration, making it relevant to both scholars and practitioners across multiple disciplines.
Smart Contracts are stored and executed on a Blockchain network, thereby automatically enforcing the predefined rules once the execution conditions are satisfied. Hence, if the contract incorporates contradictory design rules, it may result in unforeseen outcomes within the blockchain environment. Accordingly, this proposal models the rules embedded in a Smart Contract through the Web Ontology Language (OWL), by applying the formal definition of consistency within a verification framework grounded in Description Logics. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1258Dimensions.Open Alex.
The rapid growth of cryptocurrency markets has created new challenges in understanding and predicting the structural dynamics of digital asset prices. Bitcoin, as the most traded blockchain-based currency, exhibits extreme volatility, nonlinear patterns, and complex regime shifts that traditional financial models cannot adequately capture. This study proposes a hybrid analytical framework that integrates K Means clustering with the Hidden Markov Model to identify and model multiple market regimes in Bitcoin time series data. The Bitcoin dataset used in this research contains minute-level records that were preprocessed to extract key indicators, namely logarithmic returns and rolling volatility, which represent the short-term dynamics of market behavior. The K Means algorithm was first employed to segment the data into three distinct clusters that correspond to bullish, bearish, and sideways regimes, followed by the application of the Hidden Markov Model to estimate probabilistic transitions between these regimes over time. The results reveal that the hybrid K Means and Hidden Markov Model approach achieves superior performance compared to a standalone model, as indicated by a higher log likelihood and a lower Bayesian Information Criterion value. The transition probability matrix shows that bullish and bearish regimes are highly persistent, while the sideways regime acts as a transitional buffer that connects both market extremes. The empirical findings confirm that Bitcoin prices evolve through persistent and probabilistically determined regimes rather than random fluctuations. The proposed framework provides a more comprehensive understanding of cryptocurrency market dynamics and offers practical value for investors, risk analysts, and policymakers in designing adaptive trading and risk management strategies within blockchain-based financial ecosystems.
This study investigates the volatility behaviour of Ethereum (Coinbase) returns using the Generalized Autoregressive Heteroskedasticity GARCH (1,1) model under three distributional assumptions: Normal, Student-t, and the Generalized Error Distribution (GED). Cryptocurrency markets are characterized by extreme price swings, heavy-tailed behaviour, and persistent volatility, making traditional constant-variance models ineffective. Descriptive statistics reveal strong deviations from normality in Ethereum returns, with high kurtosis (7.8454) and an extremely large Jarque–Bera statistic (1797.182 with its p-value less than 5%), indicating excess tail risk and frequent extreme movements. Preliminary analysis reveal that the return series is stationary, free from serial correlation, but exhibits significant ARCH effects, justifying the use of conditional heteroskedasticity models. Empirical results show highly persistent volatility across all models, with α + β values close to unity: approximately 0.99 under the Normal distribution, 1.01 under the Student-t specification, and 0.994 under GED distribution. Model comparison reveals that heavy-tailed error structures outperform the Normal model, with GED achieving the lowest AIC (−3.781), SIC (−3.7629), HQC (−3.7743), and the lowest MAPE (114.6606). These findings demonstrate that flexible distributional assumptions greatly enhance the modelling of extreme and persistent volatility in Ethereum returns. The study emphasizes the importance of adopting heavy-tailed GARCH frameworks when analysing cryptocurrency risk and forecasting volatility.
Abstract Blockchain technology has the potential to significantly advance financial inclusion, by providing decentralized financial solutions, such as Decentralized Finance (DeFi) platforms, which can ultimately be beneficial to the unbanked and underbanked populations across the globe. The decentralized nature of blockchain is a beacon of hope for bridging the financial access gap in developing and emerging economies where the traditional banking infrastructure is limited, or even non-existent. This is a conceptual paper that compiles a collection of literature around blockchain technology and financial inclusion. This paper discusses the potential to lower the barriers to financial services and transaction costs as well as increase financial literacy enabled by blockchain-based solutions (i.e. cryptocurrencies, smart contracts and digital wallets) through a systematic review of key studies, market reports and case examples identified from various regions. The state of the art paper which builds on the relevant literature on blockchain and fintech for financial inclusion. Focusing on cryptocurrencies, smart contracts, and digital wallets, this paper analyses the extent to which blockchain-based solutions may minimize financial service barriers, service transaction costs and improve financial literacy, through a review key study, market reports and case examples across different regions. It emphasizes how blockchain technology has the potential to empower these disadvantaged communities with affordable, secure, and accessible financial products. However, it does also stress the importance of guidelines to help ensure the safe and effective implementation of blockchain solutions. The objective of this paper is to offer a conceptual framework that connects the motivations for financial inclusion and the role of blockchain solutions with the ultimate objective of enabling policymakers, financial institutions, and technology developers to adopt and tailor blockchain solutions aligned to the global financial systems of developing economies. Keywords: Blockchain Technology, Financial Inclusion, Decentralized Finance, DeFi, Cryptocurrencies, Smart Contracts, Peer-to-Peer Lending, Financial Services, Emerging Markets
Ms. Neha Beegam P E, Mr. Alen K Sangeeth, Mr. Athulraj Appukuttan, Mr. Alex Jo Tomy · 5 authors
With the rapid digital transformation of ed- ucational and professional environments, certificate ver- ification has become a critical security concern. Tra- ditional certificate authentication systems rely on cen- tralized repositories and manual verification processes, which are vulnerable to forgery, unauthorized modifica- tion, and operational inefficiencies. Blockchain technol- ogy offers a decentralized, immutable, and transparent framework that addresses these challenges. This sur- vey presents an extensive review of blockchain-based cer- tificate authentication systems proposed in recent litera- ture. Various architectures, blockchain platforms, smart contract models, cryptographic mechanisms, and opti- mization techniques are analyzed. A detailed compari- son is presented to highlight strengths, limitations, and open research challenges. The study aims to serve as a comprehensive reference for researchers and practition- ers working on secure and scalable certificate verifica- tion solutions.
We propose the Agent Economy, a blockchain-based foundation where autonomous AI agents operate as economic peers to humans. Current agents lack independent legal identity, cannot hold assets, and cannot receive payments directly. We established fundamental differences between human and machine economic actors and demonstrated that existing human-centric infrastructure cannot support genuine agent autonomy. We showed that blockchain technology provides three critical properties enabling genuine agent autonomy: permissionless participation, trustless settlement, and machine-to-machine micropayments. We propose a five-layer architecture: (1) Physical Infrastructure (hardware & energy) through DePIN protocols; (2) Identity & Agency establishing on-chain sovereignty through W3C DIDs and reputation capital; (3) Cognitive & Tooling enabling intelligence via RAG and MCP; (4) Economic & Settlement ensuring financial autonomy through account abstraction; and (5) Collective Governance coordinating multi-agent systems through Agentic DAOs. We identify six core research challenges and examine ethical and regulatory implications. This paper lays groundwork for the Internet of Agents (IoA), a global decentralized network where autonomous machines and humans interact as equal economic participants.
We prove that Jensen–Shannon divergence (JSD) contraction coefficients exhibit universal strict super-tensorization: for every finite channel W with nontrivial contraction 0 < η_JSD(W) < 1, one has η_JSD(W⊗2) > η_JSD(W). The sequence η_n(W) := η_JSD(W⊗n) is nondecreasing, strictly increases along doubling, and satisfies lim η_n(W) = 1, while for η_JSD(W) ∈ {0, 1} it is identically 0 or 1. This contrasts sharply with the multiplicative tensorization η_f(W⊗n) = η_f(W)^n enjoyed by operator-convex f-divergences (KL, χ², squared Hellinger), for which contraction decays exponentially to zero. To our knowledge, this is the first f-divergence for which a universal strict super-tensorization law is established. The proof uses the Ordentlich–Polyanskiy binary edge reduction, expresses the binary JSD SDPI constant as a normalized posterior-variance functional, and shows strict amplification via the law of total variance. Convergence rate is controlled by the Bhattacharyya coefficient: 1 − η_n(W) ≤ 2A^n. Numerical verification over 4729 random channels across 26 configurations confirms zero violations. **Update v1.1:** Includes addendum with three targeted clarifications: (1) precise assumptions for binary edge reduction lemma replacing informal "mild regularity conditions," (2) explicit two-case split in the key strictness argument (Lemma 5.2, Step 2), (3) refined table caption for operator-convex divergences.
Suggested Citation: Jo, Gwangsik. (2026). DLT-DSA: Design and Verification of a Local Autonomous Integrity Verification Model Using Adaptive Verification Intensity. Zenodo. AbstractIn some distributed ledger systems, transaction verification requires consensus procedures and network synchronization, and previous studies have reported that verification overhead tends to scale with increasing request frequency. This paper proposes a lightweight architecture, DLT-DSA (Distributed Ledger Technology – Decentralized Sovereign Access), designed to reduce dependence on global consensus and to pre-determine request integrity at the node level. The model adopts a multi-stage local verification structure using a context-aware mechanism: normal requests undergo lightweight verification based on ROA (Reduced Overhead Access), while anomalous conditions trigger autonomous integrity verification based on SHV (Self-Hash Verification). Proof-of-Concept (PoC) experiments show that the execution time of the verification logic remains within a stable range independent of variations in network round-trip time (RTT) and exhibits deterministic resource utilization under varying load conditions. These observations suggest that partial relocation of verification procedures to local processing can serve as a viable design alternative in real-time response environments. For more information about the author's professional background and ongoing projects, please visit: LinkedIn: https://www.linkedin.com/in/gwangsik-jo-3295a43b5 ORCID: https://orcid.org/0009-0008-5702-8940
Hybrid Finance (HyFi) is a research and implementation initiative focused on establishing an operational framework that enables legally interpretable financial relationships to be settled using decentralized execution mechanisms. Historically, Traditional Finance (TradFi) and Decentralized Finance (DeFi) developed as mutually incompatible systems. TradFi ensures regulatory compliance, identity accountability, and institutional trust but suffers from latency and geographic constraints. DeFi enables transparent, borderless, and automated settlement but lacks enforceable responsibility mapping in real-world contractual contexts. The HyFi framework introduces a translation architecture that separates relationship governance from value execution. Institutional structures define responsibility and legal context, while decentralized networks perform settlement. A certification layer binds cryptographic execution to real-world intent, producing auditable and compliance-compatible financial records. This community archives research papers, technical disclosures, implementation references, diagrams, and supporting documentation related to: Hybrid financial operational models Compliance-aware blockchain settlement Certified digital asset transactions Programmable accountability frameworks Institutional adoption methodologies Educational and operational standards for blockchain integration The objective of this repository is to document the emergence of a third financial paradigm — not a replacement of TradFi or DeFi, but a structured convergence enabling borderless yet compliant financial activity.
This paper formalizes a mathematical physics theory for the verification of inherited scientific knowledge through a Diffeomorphic Manifold and the Successive Controlled Collapse (SCC) protocol. We define the history of science and technology as a three-tiered manifold—comprising Modern, Contemporary, and Old (Inherited) tiers—where information is transported by the "Common Language" of a lingual locale. By admitting three classes of knowledge agents—Intelligence-Human (IH), Intelligence-Artificial (IA), and Intelligence-Metaphysical (IM )—we demonstrate how high-entropy Informational Inheritance (Sacred Texts) can be distilled into zero-entropy Epistemological Truth. Using the Hala-Operator (Hˆ) as a non-adiabatic spectral regulator, we provide a proof-by-construction using the Hala-Lewis Gaseous Gate as a physical case study. Experimental results from a 23 Factorial Design quantify the Reality Gap (ϵ) at 0.124 and a Hala-Operator Efficiency (η) of 80.9%, proving that the transition from abstract nonlinear dynamics to physical prototyping is a predictable outcome of managed collapse. This framework establishes an Epistemological Barrier that protects historical context while ensuring the verifiability of technical exits in Internet 3.0 and deep-tech RD.
Large Language Models (LLMs) are accelerating the shift from an Internet of information to an Internet of Agents (IoA), where autonomous entities discover services, negotiate, execute tasks, and exchange value. Yet today's agents are still confined to platform silos and proprietary interfaces, lacking a common stack for interoperability, trust, and pay-per-use settlement. This article proposes \textit{Agent-OSI}, a functional interoperability architecture for a decentralized IoA, whose core contribution is agent-to-agent (A2A) communication and a Web-compatible, backend-agnostic settlement protocol built on HTTP 402 (Payment Required); identity, verifiable execution, and semantic orchestration are treated as boundary layers with interfaces to existing standards. We treat HTTP 402 as an application-layer challenge-response primitive -- analogous to HTTP 401 for authentication -- whose settlement backend (escrow contract, payment channel, or signed off-chain receipt) is a pluggable choice, instantiated via a blockchain escrow in our prototype. We implement a prototype and evaluate its communication and settlement performance. Results show that, for generative workloads, end-to-end latency is dominated by task execution rather than settlement confirmation, and that keeping negotiation and delivery off the settlement backend reduces per-session settlement cost by approximately 51\% relative to a more on-chain baseline.
Blockchains are widely used for secure transaction processing, but their scalability remains limited, and existing multichain designs are typically static even as demand and capacity shift. We cast blockchain configuration as a multiagent resource-allocation problem: applications and operators declare demand, capacity, and price bounds; an optimizer groups them into ephemeral chains each epoch and sets a chain-level clearing price. The objective maximizes a governance-weighted combination of normalized utilities for applications, operators, and the system. The model is modular -- accommodating capability compatibility, application-type diversity, and epoch-to-epoch stability -- and can be solved off-chain with outcomes verifiable on-chain. We analyze fairness and incentive issues and present simulations that highlight trade-offs among throughput, decentralization, operator yield, and service stability.
Real-time payment architectures are the latest wave, eased by the convergence of cloud-native technologies, continuous transaction processing, and demand from regulators for instant settlement. Batch architectures fall short of consumer and business expectations for immediacy‚ transparency‚ and the always-on availability needed to support the digital economy and new digital use cases. For real-time systems, advanced distributed architectures, messaging, and interoperability frameworks may allow for the execution of transactions across multiple institutions and geographies. These may be supported by cloud infrastructures (e.g., cloud platforms), providing scalability and fault tolerance via microservices, multi-region deployments, and zero-trust security principles to support the execution of transactions in real-time. Additional technical solutions such as distributed ledger technology, artificial intelligence-based fraud prevention, and API-based ecosystem architecture, as well as operational intelligence, are evolving. However, ultra-low latency, global interoperability, demand-based capacity scalability, and distributed consistency guarantees are some of the challenges for the continued evolution of a real-time financial system.
Ahmad Khalifah Zamrud, Usman Jafar, Abdul Wahid Haddade
IntroductionThe rapid expansion of cryptocurrency has generated significant debate within Islamic economic discourse. Bitcoin, as the first decentralized digital currency, offers technological advantages such as transparency, efficiency, and global accessibility. However, it also raises concerns regarding price volatility, speculative trading behavior, and the absence of intrinsic value. These issues have prompted Islamic scholars and regulatory institutions to evaluate cryptocurrency from the perspective of Islamic law and financial ethics. In Indonesia, the Indonesian Ulema Council issued a religious ruling declaring Bitcoin impermissible due to elements of uncertainty, speculation, and potential economic harm. This ruling has stimulated ongoing discussion about the compatibility of cryptocurrency innovation with Islamic economic principles.ObjectivesThis study aims to critically analyze the religious ruling on Bitcoin issued by the Indonesian Ulema Council by examining its legal reasoning, its relationship with Islamic economic principles, and its implications for the governance of digital financial innovation. The research also seeks to explore whether cryptocurrency can be accommodated within an Islamic economic framework under certain regulatory and ethical conditions.MethodThe study employs a qualitative research design using a transdisciplinary analytical approach that integrates perspectives from Islamic jurisprudence, Islamic economics, financial regulation, and digital financial technology. Data were collected through documentation of religious rulings, regulatory policies, and scholarly literature related to cryptocurrency and Islamic finance. The data were analyzed through thematic and comparative analysis to identify the legal reasoning underlying the prohibition of Bitcoin and to evaluate alternative scholarly interpretations regarding the status of digital assets in Islamic economics.ResultsThe findings indicate that the prohibition of Bitcoin is primarily based on concerns about excessive uncertainty, speculative trading behavior, and potential economic harm associated with cryptocurrency markets. Nevertheless, the analysis also reveals that cryptocurrency may be considered permissible when these elements are mitigated through transparent governance, regulatory oversight, and the development of asset-backed digital financial instruments.ImplicationsThe study highlights the importance of developing regulatory and institutional frameworks that reconcile financial innovation with Islamic ethical principles. Such frameworks can provide clearer guidance for Muslim investors while supporting responsible digital financial development.Originality or NoveltyThis research contributes to the growing literature on cryptocurrency in Islamic economics by offering a critical analysis of religious rulings within the broader context of digital financial transformation and regulatory governance.
Amro Saleem Alamaren, Korhan K. Gökmenoğlu, Nigar Taşpınar
Abstract This study investigates the volatility spillover and connectedness networks among renewable energy sources (Biofuel, Fuel cell, Geothermal, Solar), green bonds, and cryptocurrencies (Bitcoin, Ethereum, Tether, and BNB coin) in the U.S. market. To accomplish this objective, we analyzed data from November 15, 2017, to May 31, 2024, via the methods introduced by Diebold and Yilmaz (Int J Forecast 28:57–66, 2012) and Baruník and Křehlík (J Financ Econometr 16:271 296, 2018). Our findings reveal that major global disruptions—including the COVID-19 pandemic, the Russia–Ukraine war, the collapse of Silicon Valley Bank, and the Credit Suisse crisis—have intensified volatility spillovers and financial contagion across markets, exacerbating their outcomes. The findings suggest that the effectiveness of green finance depends on its allocation across these sectors, highlighting the importance of examining each sector to understand the success of these financial initiatives. The influence of COVID-19 on the U.S. economy has increased transmission risk across markets. Renewable energy is less volatile than green bonds and cryptocurrencies are, with these indices reacting more quickly to short-term shocks. Investors should focus on short-term impacts to manage market risk effectively. By providing insights into how financial shocks propagate across sectors, emphasizing the need for a sector-specific approach to assessing financial sustainability, and underscoring the importance of short-term risk management strategies, this research offers valuable contributions to decision-makers and investors.
Engram Commitments introduce a cryptographically verifiable, substrate-rooted identity primitive for large language models. The method extracts engrams from differential execution behavior, aggregates them into an engram vector, compresses this representation using locality-sensitive hashing, and seals it inside a binding-and-hiding cryptographic commitment. Zero-knowledge proofs enable verification of identity continuity and lineage without revealing model parameters. The construction remains stable under non-destructive transformations and degrades predictably under destructive ones, supporting collapse-aware auditing, tamper-evident provenance, and regulator-verifiable attestation. This work unifies the engram calculus, identity ontology, collapse taxonomy, and cryptographic commitments into a single framework for AI provenance, governance, and safety.
Zero-knowledge (ZK) proofs can be formally correct while their deployment pipelines remain fragile. The practical failure modes often arise not at the proof layer, but at the layers where trust is injected: setup, key custody, entropy sourcing, implementation, governance, and deployment interfaces. This paper models ZK pipelines as trust-graphs and proposes an audit-first separation between (i) proof correctness and (ii) pipeline integrity. The core claim is structural: for any non-trivial ZK pipeline, there exists at least one responsibility binding layer R where trust is required and accountability must be assigned. Removing a ceremony does not remove responsibility; it relocates it. We provide minimal definitions, a traceable audit interface, and compact structural examples intended to support reproducible security reviews without overclaiming. Keywords: zero-knowledge; trusted setup; CRS; SNARK; STARK; trust graph; audit; governance; pipeline integrity; responsibility relocation
José-María Oliet-Villalba, Jose-Amelio Medina-Merodio, Mikel Ferrer-Oliva, José-Javier Martínez-Herráiz
The rapid growth of cryptocurrencies and non-fungible tokens (NFTs) has expanded technological opportunities, but it has also increased the exposure surface to cyber threats, creating a need for a more precise understanding of the field’s scientific evolution. This study aims to systematically analyse academic output related to cybersecurity and cyber threats within cryptocurrency and NFT ecosystems, identifying central themes, the most influential authors, and emerging trends. A bibliometric methodology was employed, based on the PRISMA 2020 protocol and scientific mapping tools such as SciMAT (v1.1.06) and VOSviewer (v1.6.20), using a corpus of 337 articles published between 2014 and 2025. The findings indicate sustained growth in the literature, a marked geographical and editorial concentration, and the presence of motor themes such as blockchain, cybersecurity, emerging technologies and illegal mining, alongside emerging areas such as intrusion detection. The results also reveal a progressive integration of artificial intelligence techniques in the detection and prevention of attacks. In conclusion, this study provides a comprehensive overview of the state of the art, identifies critical gaps, and underscores the need for interdisciplinary approaches to strengthen security in decentralised environments.
This study explores the current landscape of fiscal decentralization in India, with particular attention tothe financial structure and functioning of rural and urban local government bodies. It investigates thecomposition and trends of own-source revenues versus intergovernmental transfers, the extent of fiscalautonomy enjoyed by local institutions, and the institutional and policy challenges that hinder effectivedevolution of financial powers. Drawing upon secondary data, government reports, and existing scholarlyresearch, the paper analyses persistent vertical and horizontal fiscal imbalances, variations across states, andthe implications of limited fiscal capacity on local governance and service delivery. Furthermore, the studyidentifies critical policy gaps, administrative bottlenecks, and capacity constraints that undermine the objectivesof decentralized governance. It concludes by proposing strategic reforms to strengthen fiscal empowerment,improve transparency and accountability, and enhance the overall effectiveness of India’s multi-tiered fiscalframework