Chukwuebuka Francis Ikenga-Metuh, Abel Yeboah-Ofori
Background: Blockchain technology has emerged as a transformative communication solution for securing distributed systems. However, several vulnerabilities exist during transactions, including latency and network congestion issues during mempool processing, topology weaknesses, cross-chain bridge exploits, and cryptographic weaknesses. These vulnerabilities have led to attacks that have threatened system integrity, including Block Extractable Value (BEV) attacks, Maximal Extractable Value (MEV) attacks, sandwich attacks, liquidation, and Decentralized Finance (DeFi) reordering attacks, among others. Thus, implementing a robust security framework based on the Confidentiality, Integrity, and Availability (CIA) triad remains critical for addressing modern blockchain technology threats. Objective: This paper examines blockchain technology, its various vulnerabilities, and attacks to determine how criminals exploit the system during transactions. Further, it evaluates its impact on users. Then, implement a blockchain attack in a “MasterChain” virtual environment to demonstrate how vulnerable spots can be practically exploited and discuss the application of the CIA security triad through modern cryptographic primitives. Methods: The approach considers Hevner’s design science framework, which emphasizes creating innovative artifacts that address identified problems while contributing to the knowledge base through rigorous evaluation. Furthermore, we developed a MasterChain tool using Python with Flask for distributed node communication, utilizing the Elliptic Curve Digital Signature Algorithm (ECDSA) with the Standards for Efficient Cryptography Prime 256-bit Koblitz curve 1 (secp256k1) for digital signatures and Secure Hash Algorithm 3 (SHA-3) (Keccak-256) hashing for block integrity. Results: show how the CIA has been implemented to provide secure communication through ECDSA-based transactions, SHA-3 chain integrity verification, and a multi-node distributed architecture, respectively. The performance analysis shows that ECDSA provides 256-bit security with 64-byte signatures compared to 2048-bit Rivest–Shamir–Adleman (RSA)’s 256-byte signatures, achieving a 75% reduction in bandwidth overhead. SHA-3 provides immunity to length extension attacks while maintaining equivalent collision resistance to SHA-256. Conclusions: The MasterChain framework provides a practical foundation for implementing blockchain security that addresses both classical and emerging vulnerabilities. The adoption of ECDSA and SHA-3 (Keccak-256) positions the system favourably for modern blockchain applications, while providing insights into the cryptographic trade-offs between performance, security, and compatibility.
Abstract This study explores transformation of business and IT through the lens of five emerging technology fields: artificial intelligence, Machine Learning, Data Analytics, Data Science and Blockchain. The contemporary business landscape is undergoing a profound transformation driven by the convergence AI, ML, DS, DA, and Blockchain technology. Individually, these technologies offer significant advancements: AI and ML provide sophisticated decision- making and automation capabilities, while data analytics and data science extract actionable insights and non-obvious patterns from vast datasets. Blockchain technology, a decentralized and immutable ledger, establishes a foundation of trust, transparency, and security in data management and transactions. By facilitating automation, data-driven decision-making and Data security all the above technologies transforming number of industries. The synergistic integration of these technologies creates novel business models and powerful operational enhancements in smart contract, Data sharing, Decentralized AI Marketplaces, cybersecurity. Important methods to use with these technology are covered including supervised learning, unsupervised learning, deep learning, descriptive analytics, predictive analytics, prescriptive analytics and distributed ledger technology. The challenges are also discussed, such as data privacy and quality, high cost, skill gap and interoperability. This study highlights opportunities and challenges in current trends available in AI, ML, DA, DS and Blockchain on business and IT sector. Though challenges related to scalability, regulatory compliance, and implementation complexity exist, ongoing technological advancements are actively addressing these barriers. It will be overcome by doing a thorough assessment of recent studies and identifying the potential benefits, impacts, and future directions of all the five technologies.
Abstract In the decade since the adoption of the United Nations’ 2030 Agenda, India has transitioned from a passive participant to a global architect of sustainable development. This paper explores the intricate mapping of Sustainable Development Goals (SDGs) onto India’s macroeconomic policies. It examines how the "Saptarishi" priorities of the Union Budget and the decentralization of targets through NITI Aayog have created a unique "Indian Model" of development. While progress in clean energy (SDG 7) and digital inclusion (SDG 8) has been exemplary, the paper highlights the persistent challenges of climate-induced agricultural volatility and the financing gap.
Smart contract is a type of contract that exercised automatically if requirements are met in trades, the data on chains is available at all time and no edit or central authority intervene is allowed. In China, SMEs often face high requirement of lending from bank, information asymmetry and region difference when financing. In this research, it is proved that smart contracts reduce SME financing cost via lowering human labour and spend time, which is one of reasons that smart contracts and blockchain are welcomed in SMEs. The government should set related regulations on smart contracts and technical designers need to improve systems in the future so that more SMEs could get benefits during financing programs.
Recent disclosures of industrial-scale knowledge distillation — including campaigns comprising millions of fraudulent API exchanges targeting frontier models [Anthropic, 2026] — have made post-hoc detection of model theft a critical security requirement. Building on a formally-verified framework of log-prob order-statistic geometry, we investigate the adversarial resilience of neural network identity across 72 experimental checkpoints. We establish a Two-Layer Identity Hypothesis: a model’s structural identity (weights-regime geometry) is empirically invariant to distillation (within acceptance threshold epsilon across all 18 protocols), while its functional identity (API-regime Poisson Point Process residuals) predictably transfers to the student, converging up to 52% toward the teacher’s template. Stress-testing this forensic channel against a white-box adversary, we find that functional provenance is geometrically coupled to the knowledge transfer objective. Adversarial erasure gradients are consistently dominated by the distillation loss, achieving only a transient suppression that rebounds within one epoch. Passive fine-tuning on fresh data erases the trace more effectively than any adversarial method, but at a measurable cost to general capability — revealing a Pareto frontier with no favorable region for the adversary. This establishes API forensics as a time-sensitive detective control (“The Tripwire”) and weights-regime identity as the immutable anchor (“The Vault”). Finally, we observe an apparent vulnerability: a cross-family adversarial spoofing attack achieves 69.4% convergence toward a decoy’s fingerprint, while same-family spoofing catastrophically fails. We resolve this paradox by mapping the PPP-residual vector space, revealing that models cluster by capability topology, not corporate lineage. Cross-family “spoofing” is a spatial illusion caused by a narrow 7.8 degree alignment between the decoy and the primary distillation trajectory (R2 = 0.995), whereas same-family decoys are anti-aligned. Across all adversarial interventions, the underlying Gumbel universality (delta_norm) remains invariant (CV = 1.9%). We conclude that during active distillation, an adversary cannot simultaneously acquire a teacher’s capabilities and erase or redirect the forensic trace. In this setting, the geometry forbids it. The Neural Network Identity Series — Mathematical foundations, empirical validation, and governance frameworks for verifying which model is running Newest addition: Technical Note: The Disappearing Window — AI Logprob Access Withdrawal and the Structural Verifiability of Frontier Model Contracts (DOI: 10.5281/zenodo.20362098) Paper 1: The δ-Gene: Inference-Time Physical Unclonable Functions from Architecture-Invariant Output Geometry (DOI: 10.5281/zenodo.18704275) Paper 2: Template-Based Endpoint Verification via Logprob Order-Statistic Geometry (DOI: 10.5281/zenodo.18776711) Paper 3: The Geometry of Model Theft: Distillation Forensics, Adversarial Erasure, and the Illusion of Spoofing (DOI: 10.5281/zenodo.18818608) Paper 4: Provenance Generalization and Verification Scaling for Neural Network Forensics (DOI: 10.5281/zenodo.18872071) Paper 5: Beneath the Character: The Structural Identity of Neural Networks — Mathematical Evidence for a Non-Narrative Layer of AI Identity (DOI: 10.5281/zenodo.18907292) Paper 6: Which Model Is Running?: Structural Identity as a Prerequisite for Trustworthy Zero-Knowledge Machine Learning (DOI: 10.5281/zenodo.19008116) Paper 7: The Deformation Laws of Neural Identity (DOI: 10.5281/zenodo.19055966) Paper 8: What Counts as Proof? — Admissible Evidence for Neural Network Identity Claims (DOI: 10.5281/zenodo.19058540) Paper 9: Composable Model Identity — Formal Hardening of Structural Attestations in the Enterprise Identity Stack (DOI: 10.5281/zenodo.19099911) Paper 10:Where Identity Comes From: Path Sensitivity and Endpoint Underdetermination in Neural Network Training (DOI: 10.5281/zenodo.19118807) Paper 11: Post-Hoc Disclosure Is Not Runtime Proof: Model Identity at Frontier Scale (DOI: 10.5281/zenodo.19216634) Paper 12: Family-Dependent Response to Reasoning Distillation Across Structural and Functional Identity Layers (DOI: 10.5281/zenodo.19298857) Paper 13: Safety-Alignment Removal as a Model-Identity Failure — Structural Evidence from Published Weight-Level Mutation Checkpoints (DOI: 10.5281/zenodo.19383019) Technical Note: Agent Identity Is Not Model Identity (DOI: 10.5281/zenodo.19240883) Technical Note: Gap Invariance: Why PPP Measurements Are Domain-Independent by Construction (DOI: 10.5281/zenodo.19275524) Technical Note: Measured Model Substitution Under Valid Agent Credentials (DOI: 10.5281/zenodo.19342848) Technical Note: Artifact Identity Is Not Runtime Identity — Trustfall Lite and the Boundary of File-Level Model Verification (DOI: 10.5281/zenodo.20019127) Formal Verification Stack for Neural Network Structural Identity (IT-PUF Coq Proofs) (DOI: 10.5281/zenodo.18930621) Copyright (c) 2026 Anthony Ray Coslett / Fall Risk AI, LLC. All Rights Reserved. Confidential and Proprietary. Patent Pending (Applications 63/982,893, 63/990,487, 63/996,680, 64/003,244).
Abstract Blockchain technology is emerging as a transformative innovation in the field of accounting by enhancing transparency, accuracy, and reliability of financial information. Traditional accounting systems often face challenges such as data manipulation, lack of real-time reporting, and dependence on centralized control. Blockchain, with its decentralized and immutable nature, provides a secure platform for recording financial transactions in a transparent and verifiable manner. Each transaction is recorded in a distributed ledger that cannot be altered without consensus, reducing the chances of fraud and errors. This technology also supports real-time data sharing among stakeholders, improving trust and accountability in financial reporting. The study explores how blockchain can improve accounting practices, auditing processes, and financial decision-making while highlighting its benefits, challenges, and future potential in the accounting profession.
Objective: This study aims to evaluate the effectiveness of regulatory models across selected jurisdictions such as the United States, Brazil, China, Thailand, Indonesia, and the European Union and to analyze emerging trends in crypto-related economic crime, particularly in relation to implementation gaps in FATF Recommendation 15, namely the Travel Rule, and the resulting cross-jurisdictional regulatory arbitrage dynamics. Research Design & Methods: This study uses a comparative qualitative approach through document analysis and cross-country case studies. Secondary data comes from FATF, Interpol, UNODC, Chainalysis reports, national regulations, and academic literature, which are analyzed using thematic content analysis and comparative regulatory analysis. Findings: Research findings indicate that regulatory fragmentation and gaps in the implementation of FATF standards create regulatory arbitrage loopholes that are exploited by crypto criminals. Crypto crime in the 2024-2025 period is becoming more professionalized, marked by the dominance of stablecoins, the involvement of state actors, and low asset recovery rates. Network-based international investigative cooperation, has proven to be more adaptive than unilateral repressive approaches. Implications: There is a need for harmonization of cross-border AML policies, acceleration of Travel Rule implementation, and strengthening of informal investigative cooperation mechanisms and public private partnerships with VASPs to improve the effectiveness of asset tracing and recovery. Contribution & Value Added: This study enriches the literature on digital economic crime by linking regulatory arbitrage and FATF networked governance, and provides the latest empirical evidence for the formulation of adaptive AML policies in the era of decentralized finance.
Abstract The rapid expansion of cryptocurrency markets has significantly transformed global financial systems through the adoption of decentralized, blockchain-based transaction mechanisms. Digital assets such as Bitcoin and Ethereum operate on distributed ledger technology, which enhances transparency, immutability, and peer-to-peer verification without reliance on traditional financial intermediaries. Despite these technological advancements, the cryptocurrency ecosystem faces escalating cybersecurity risks that threaten the integrity of financial data and reporting systems. Cryptocurrency exchanges, digital wallets, custodial services, and decentralized finance (DeFi) platforms are increasingly targeted by cybercriminals through hacking, phishing schemes, ransomware attacks, private key theft, and smart contract vulnerabilities. These cybersecurity incidents have profound implications for financial record integrity, including unauthorized transactions, asset misappropriation, valuation distortions, and inaccuracies in financial statements. Unlike conventional banking systems, cryptocurrency transactions are often irreversible, amplifying the financial and accounting consequences of cyber breaches. Furthermore, the pseudonymous nature of blockchain transactions complicates audit verification, regulatory compliance, and internal control processes. As organizations integrate digital assets into their financial reporting frameworks, weaknesses in cybersecurity governance may undermine stakeholder confidence and market stability. This paper critically examines the major cybersecurity threats present in cryptocurrency markets and evaluates their direct and indirect impact on the reliability, accuracy, and auditability of financial records. It also analyzes existing risk mitigation strategies, including multi-factor authentication, cold storage solutions, encryption protocols, smart contract audits, and regulatory oversight mechanisms. The study concludes that while blockchain technology inherently promotes data immutability and transparency, systemic vulnerabilities at exchange, platform, and user levels continue to pose substantial risks. Strengthened cybersecurity governance frameworks, standardized accounting treatments for digital assets, and coordinated global regulatory efforts are essential to ensuring the long-term integrity and sustainability of cryptocurrency-based financial systems.
The stability of global financial markets is increasingly threatened by rapid liquidity cascades, manifesting empirically as instantaneous "Flash Crashes." Current quantitative risk models, such as Value-at-Risk (VaR) and the Efficient Market Hypothesis (EMH), assume continuous liquidity and treat extreme volatility as probabilistic statistical anomalies based on historical distributions. These models fundamentally lack a deterministic, geometric boundary for limit-order book coherence. This paper introduces a strict topo-dynamical framework for financial network scaling. By modeling the market structure as a spatial competition between the geometric propagation of liquidity and localized volatility shocks, we derive a universal square-root geometric invariant (ℓmarket). We provide an intuitive translation of this threshold, explicitly dissect the failure of VaR during the May 2010 Flash Crash, and map the invariant across both traditional equities and Decentralized Finance (DeFi) Automated Market Makers (AMMs). Finally, we present a hardware-aware (FPGA) blueprint for Active Liquidity Throttling (ALT), acknowledging systemic implementation risks and regulatory hurdles.
Kenneth Richard Dike, Ugbari Augustine, Martha Ozohu Musa
Delays and security remain major issues in traditional manual voting, while in the emerging electronic voting, trust and privacy remain issues in its adoption. This research presents the design and development of a secure electronic voting protocol that combines biometric verification of a standard identity with cryptography to preserve election integrity. This research follows the Design Science Research Methodology, producing the protocol as an artefact, beginning with quick work on it and iteratively improving it during development. The proposed architecture uses a combined National Identity verification and Liveness detection procedure for user authentication, ensuring voter uniqueness and preventing impersonation. It also integrates the RSA blind signature protocol to prevent direct linking of votes to their voters. It uses Paillier encryption to safeguard votes both in transit and at rest, and this encryption scheme has a homomorphic property that enables aggregation of encrypted votes and decryption of the final tally. It uses the SHA-256 cryptographic hashing algorithm, the HMAC authentication technique and the AES-GCM encryption to secure the integrity of data. It also uses zero-knowledge proofs to demonstrate the correctness of encrypted votes and decrypted tallies. Testing showed that it prevented a photo spoofing attempt and also blocked authentication using a person’s mother’s identity data. Also, when the blinded vote is compared with the unblinded, via local logs on the development system, there is no direct link. The whole system shows a secure electronic voting protocol that is easy to use and can be trusted.
This paper examines the critical role of education in fostering decentralized finance (DeFi) and cryptocurrency literacy. Drawing on qualitative interviews with industry professionals and educators, the study explores how formal education, online learning, and peer-to-peer knowledge sharing shape public understanding of DeFi systems. The findings highlight that limited access to structured educational resources hinders the adoption of crypto technologies, especially in emerging economies. Interviewees emphasized the importance of learning environments that not only teach technical concepts but also explain the risks, use cases, and ethical dimensions of decentralized technologies. While online communities and social media platforms offer learning opportunities, they also expose users to misinformation and hype-driven content. The paper advocates for integrating blockchain topics into academic curricula and promoting accessible digital literacy initiatives to support inclusive participation in the evolving financial ecosystem. It also suggests that governments and educational institutions partner with fintech innovators to create standardized, multilingual, and culturally adaptive learning content. By improving blockchain literacy through both formal and informal educational channels, the industry can close the knowledge gap, increase responsible adoption, and reduce the digital divide in the global financial system (Prajapati, 2025). This research contributes to the understanding of how knowledge dissemination strategies influence technology adoption in disruptive finance sectors.
In classical electrodynamics, complex constitutive parameters encode both dispersive and dissipative behavior of matter under electromagnetic excitation. The real component of the permittivity governs reversible polarization and energy storage, while the imaginary component governs irreversible transfer of field energy into microscopic degrees of freedom. This work presents an interpretive clarification: the imaginary component may be read as a structural ledger of irreversible participation already embedded within the electromagnetic response formalism. Without modifying Maxwell’s equations, conservation laws, or thermodynamic principles, this perspective makes explicit that dissipation and irreversibility are not appended phenomenologically but arise directly from constitutive closure in linear response theory. The analysis further distinguishes between the magnitude and the spatial distribution of irreversible participation, introducing a participation-ratio diagnostic to characterize whether dissipation remains distributed or becomes localized under constraint. This distinction clarifies how coherent structure may persist despite finite loss, and why structurally localized dissipation can lead to instability or transition even when total energy loss is unchanged. The contribution is strictly interpretive, providing a conceptual bridge between electromagnetic response theory and constraint-based descriptions of persistence and irreversibility within established physics.
The development of blockchain technology encourages the use of smart contracts as digital contract instruments that are automatic and cannot be changed, especially in cross-sector commercial transactions. This study aims to analyze the legal status of blockchain-based smart contracts as well as evaluate the possibility of their integration in legally recognized commercial contract dispute resolution mechanisms. This research uses a normative legal research method with a conceptual and case legislation approach conducted through a literature study of laws and regulations, legal doctrine, as well as relevant decisions and cases. This study does not involve respondents or informants because it focuses on the analysis of legal norms and concepts. The data was analyzed qualitatively juridically through interpretation methods and legal arguments. The results of the study show that smart contracts can in principle be integrated in the settlement of commercial contract disputes as an instrument for the implementation and proof of contracts, but have not been able to fully replace the role of conventional dispute resolution mechanisms due to their limitations in handling legal interpretation, the application of the principle of good faith, and certain conditions such as non-technical defaults. This study concludes that the integration of smart contracts requires a hybrid model that combines technology-based automated execution with a law-based dispute resolution mechanism to ensure legal certainty and substantive justice in commercial contract practice.
The development of blockchain technology has introduced smart contracts as a new form of automated commercial agreement. Smart contracts are self-executing programs that perform contractual obligations when predetermined conditions are met, reducing the need for intermediaries and increasing efficiency in commercial transactions. Their growing use raises important legal questions regarding their validity and enforceability under existing legal systems, particularly under U.S. commercial law. This article examines the legal nature and enforceability of smart contracts within the framework of United States commercial law. It analyzes whether smart contracts satisfy the essential elements of contract formation, including offer, acceptance, consideration, and mutual assent. The article also explores the applicability of the Uniform Commercial Code (UCC) and its role in recognizing electronic and automated agreements. The article concludes that smart contracts can be legally enforceable under U.S. commercial law if they meet traditional contract requirements. Existing legal principles are flexible enough to accommodate smart contracts, making them a reliable tool for modern digital commerce.
This paper provides a theoretical and methodological basis for aligning digital tax control technologies with tax policy principles in Russia and Tajikistan. This study’s value and innovation stem from tax control’s digital shift and linking tech to tax system principles. The object of the study is tax relations and tax administration practices in the digital transformation of public administration in the Russian Federation and the Republic of Tajikistan. The subject of the study is the theoretical and methodological foundations for aligning digital tax control technologies, such as big data, AI, distributed ledgers, the Industrial Internet of Things, and analytical platforms, with the fundamental principles of state tax policy. The research aims to develop the conceptual contours of the theoretical and methodological study and a mechanism for aligning digital tools and tax policy principles, as well as to identify the institutional, legal, axiological, and process conditions that determine the feasibility and limits of integrating digital control tools into the tax systems of Russia and Tajikistan. The study employed abstract and conceptual analysis, a source review and synthesis, theoretical modeling, and generic scientific methods . The author focused on analyzing and assessing digital tools’ compliance with legal, neutral, transparent, predictable, efficient, and fiscally sustainable principles. The work’s finding is a conclusion: there are methodological limitations in the digitalization of tax control. The author presented a conceptual system, highlighted research areas, and called for framework development. This study covers boosting strategic digital tax solutions, tax policies, the digital transformation of tax authorities, and digital tax control systems.
The article presents a comprehensive study of the transformation of intergovernmental fiscal relations in Ukraine under the dual influence of the fiscal decentralization reform of 2014–2020 and the unprecedented wartime shock of 2022–2025, alongside the emergence of a donor-conditional post-war reconstruction architecture. The author delineates the basic categories: intergovernmental fiscal relations, fiscal federalism, fiscal and budgetary decentralization. The author substantiates the thesis that the Ukrainian reform implemented predominantly budgetary rather than fiscal decentralization due to the dominance of shared taxes without local control over the base and rate. The impact of Law No. 3428-IX, which redirected the «military» personal income tax to the state budget from 1 October 2023, and the freezing of the reverse subvention is analyzed as an institutional precedent that distorts horizontal equalization. Growing territorial disparities are identified between the capital (39 % of municipal-level revenues in 2024), western agglomerations, and frontline communities that lost up to 45 % of revenues. The article reveals the risks of a «two-channel» community financing system through the Ukraine Facility of 50 billion euros for 2024–2027, the World Bank SURGE programme, and the European Investment Bank instruments. The author proposes a hybrid model of transformation of intergovernmental fiscal relations involving a differentiated PIT allocation rate depending on the status of the community, the replacement of the reverse subvention with a territorial solidarity fund based on a multifactor distribution formula, and an integrated project cycle with external donor instruments. Six substantive theses concerning the further architecture of the system are formulated with reference to the fiscal rules of the European Union and the subsidiarity principle of the European Charter of Local Self-Government. Particular attention is paid to the institutional strengthening of the meso-level following the Polish experience of establishing regional accounting chambers and associations of self-government.
This study aims to examine the development and structure of global research on Sharia finance through a bibliometric analysis of publications indexed in the Scopus database from 2010 to 2024. Using bibliometric techniques and visualization tools such as VOSviewer, this study analyzes publication trends, collaboration networks among authors, institutions, and countries, as well as the thematic evolution of research topics in the field of Islamic finance. The results indicate that research on Sharia finance has grown significantly during the observed period, reflecting the increasing global importance of Islamic financial systems. The collaboration analysis shows that several key authors and institutions play central roles in connecting different research groups, while countries such as Indonesia, Malaysia, Saudi Arabia, the United Kingdom, and the United States emerge as important contributors to the global research network. Keyword co-occurrence analysis reveals that dominant themes include Islamic banking, Sharia compliance, financial institutions, and Islamic law. At the same time, emerging topics such as financial technology (fintech), blockchain, decentralized finance, and financial inclusion indicate a shift toward digital transformation and innovation in Islamic financial services. Furthermore, themes related to sustainable development, ESG, and waqf highlight the growing integration of Islamic finance with broader sustainability and ethical finance agendas. This study provides a comprehensive overview of the intellectual structure, collaboration patterns, and emerging research trends in Sharia finance, offering valuable insights for future academic research and policy development in the global Islamic financial industry.
We present APIS v2.0 (Agent Passport Issuance Standard), a cryptographic identity framework for autonomous AI agents operating across organizational boundaries and agentic frameworks. APIS v2.0 defines a credential chain grounded in legal mandate doctrine, hardware trust anchors (TPM 2.0), and DNS-anchored identity for cloud-hosted agents. Each agent receives a realm-scoped Decentralized Identifier (DID) and a signed Passport JWT binding the agent to a named principal, a scoped mandate, and a verifiable machine identity. The framework introduces a tiered trust model accommodating physical TPM (Tier 1) through DNS-registered identity (Tier 2.5), enabling CMMC Level 2 compliance for AI agent operations. We describe the APIS-APP provisioning protocol — an ACME-equivalent automated passport issuance mechanism — and demonstrate interoperability across OpenHands, Claude Code, Codex, and custom agent frameworks. A reference implementation is available at passportalliance.org.
Every standard signature scheme enforces one property: only the key holdercan sign. What the key holder signs is unconstrained. Policy enforcement-- spending limits, rate limits, access control -- lives in smartcontracts, middleware, or governance: layers that can be upgraded,bypassed, or exploited. We call this the software-layer assumption:compliance holds only if the enforcing code is correct and unmodified. We eliminate this assumption. We introduce behavior-bound signatures(BBS), in which a policy constraint delta(x) < epsilon is committed atkey generation and enforced inside the signature's zero-knowledge proof.If the action violates the policy, the ZK constraint system isunsatisfiable -- no witness, no proof, no signature. This is not asoftware check. It is a mathematical impossibility. No software canoverride. Unlike policy-based signatures (where an authority imposes policy onsigners), BBS is self-committed: the signer binds their own futurebehavior at key generation, and even the signer cannot later violate orrevoke this commitment. We formalize this as policy-soundness (PS-CMA), a security modelstrictly stronger than EUF-CMA, and prove it under standard assumptions(Pedersen binding, Poseidon CR, ZK knowledge soundness). From thissingle primitive, five independent consequences follow -- not as separatedesigns, but as necessary implications of one cryptographic root: (A) Compliance safety under f <= n-1 Byzantine faults, decoupled from honest-quorum assumptions.(B) O(1) verification and audit via a single ZK check and Pedersen homomorphic aggregation.(C) Elimination of the virtual-machine execution layer for policy-constrained transactions.(D) A gasless ledger: branch C removes metering, while ZK-encoded rate limits make spam mathematically nonexistent.(E) The first cryptographic guarantee that a compromised autonomous AI agent cannot exceed its authorized behavioral envelope. Moreover, the zero-knowledge property ensures that complianceverification reveals neither the signer's identity nor the transactionparameters -- achieving regulatory compliance without identitydisclosure, complementary to existing ZK-KYC frameworks that verifystatic identity attributes.
The security and integrity of medical record data is a crucial issue in the era of healthcare service digitalization. Traditional systems still face risks of manipulation, information leaks, and issues with interoperability between healthcare institutions. Blockchain technology has emerged as a promising solution to address this issue thanks to its features of decentralization, openness, and difficulty in modification. One consensus method that can be applied is Proof of Work (PoW), which has proven to maintain the authenticity of transactions on a distributed network. This research aims to design and evaluate a blockchain-based medical record application using the PoW consensus algorithm to ensure the security, transparency, and reliability of medical data storage. The approach used is experimental, involving the development of a blockchain-based application prototype. The PoW algorithm is applied to ensure the validity of medical record data transactions. The evaluation was conducted by measuring the security aspect (resistance to data changes), performance (time to verify transactions), and scalability (number of transactions that can be handled). The results of the experiment show that implementing PoW in a medical record system can maintain data integrity with a high level of resistance to unauthorized changes. The average time for transaction verification is 2.4 seconds per block, with the ability to handle up to 150 transactions per minute. Although the performance of PoW requires significant computational resources, the level of security it offers suggests potential for implementation in larger healthcare systems. The application of blockchain with the PoW algorithm to medical records has proven to improve the security and transparency of medical information. This research successfully met the established objectives, although computational efficiency issues still need to be addressed. Further research is suggested to explore other consensus algorithms such as Proof of Stake (PoS) or Practical Byzantine Fault Tolerance (PBFT) to improve performance without sacrificing security aspects. Keywords: Blockchain, Electronic Health Records (EHR), Proof of Work (PoW), Smart Contract, Healthcare Information System
Cloud computing has transformed data storage, accessibility, and enterprise operations; however, it has also increased exposure to sophisticated cyber threats. Traditional centralized Identity Management Systems (IDMs) often suffer from critical vulnerabilities such as a single point of failure, where the compromise of a central authority can expose sensitive user credentials. This research proposes ZKP-Shield, a security framework that integrates Non-Interactive Zero-Knowledge Proofs (NIZKPs) with a Software-Defined Perimeter (SDP) to create a secure and invisible cloud authentication environment. The proposed architecture eliminates the need to transmit passwords or sensitive identity data by allowing users to mathematically prove their identity without revealing secret information. Simultaneously, the SDP layer conceals cloud resources from unauthorized users by enforcing a “dark cloud” model, where services remain hidden until authentication is successfully verified. The framework employs cryptographic techniques such as the Discrete Logarithm Problem and the Fiat–Shamir heuristic to transform interactive proofs into efficient non-interactive authentication processes. Experimental simulations conducted in a distributed cloud environment demonstrate that the ZKP-SDP integration significantly reduces attack surfaces, prevents credential-based attacks, and maintains acceptable latency for enterprise applications. The results indicate that combining cryptographic identity verification with network invisibility provides a scalable and resilient security model for modern cloud infrastructures.
The global logistics sector is confronted with crucial data reliability challenges wherein traditional centralized systems have a 15-20% manual error rate and are highly susceptible to counterfeiting. In this regard, the current research proposes Sentinel, a decentralized supply chain tracking framework utilizing the Polygon Proof-of-Stake blockchain coupled with smart contracts in Solidity for granting immutability to data governance. It follows a hybrid architecture wherein on-chain cryptographic verification is coupled with MongoDB for high-speed off-chain data retrieval. Extensive performance testing was performed on a simulated supply chain network with 10,000 transaction cycles of creation, transfer, and delivery. It shows that Sentinel has been able to achieve 100% in data integrity, thus rejecting all 500 unauthorized ledger modifications attempted during security stress testing. In terms of efficiency, the proposed framework minimized data retrieval latency to less than 180 ms, which was an improvement of 92% compared to traditional decentralized architectures. Additionally, it minimized the transaction cost to roughly ₹0.45/unit, thus offering a cost reduction of about 99.9% compared to traditional Ethereum Layer-1 implementations.
Modern insurance organizations have adopted artificial intelligence in narrow, task-specific roles, resulting in fragmented systems that optimize isolated functions without fundamentally reshaping the underwriting and claims lifecycle. This “incrementalism” yields a human-default, sequential process plagued by structural bottlenecks, inconsistent risk evaluation, and limited transparency. This paper introduces NEXUS (Next-Generation Executive Underwriting and Settlement Intelligence), a framework to re-architect insurance as an AI-native system. NEXUS transitions AI from a peripheral tool to the primary orchestrator of end-to-end processes, conceptualizing the insurance lifecycle as a conversational, agent-orchestrated workflow. It is realized through a unified conversational interface that coordinates a decentralized ecosystem of specialized, collaborative AI agents each responsible for domain-specific reasoning such as geospatial risk assessment, financial verification, or medical outcome analysis. The central innovation is the Truth Score Engine (TSE), a governance-first aggregation mechanism that non-linearly synthesizes agent outputs by weighting evidentiary provenance, confidence estimates, and cross-agent consistency. The TSE governs decisions via a Three-Tiered Confidence Protocol: • High Confidence (&gt;90%) validates outcomes for immediate human sign-off without re-verification; • Medium Confidence (60-90%) routes decision summaries for targeted human review of specific flags; • Low Confidence (&lt;60%) escalates cases as ‘’Risky,’’ reverting to traditional manual investigation. This protocol yields a single, auditable decision artifact while preserving full traceability of the reasoning pathway. By embedding multi-agent coordination, contextual awareness, and tiered governance at the architectural level, NEXUS demonstrates a scalable pathway toward adaptive, transparent insurance systems. It ensures precision, combats fraud, and dramatically reduces settlement time, positioning AI-native governance as a foundational requirement for deploying trusted, autonomous decision-making in high-stakes financial domains.
Abstract The rapid evolution of computer technology is changing digital ecosystems, business processes, governmental operations, and how humans use computers to perform tasks. This paper is a comprehensive analysis of modern computer technology trends, including advancements in artificial intelligence; cloud computing; edge computing; the internet of things (IoT); 5G networks; blockchain; cybersecurity; quantum computing; emerging technologies such as immersive technologies and robots; big data; and sustainable computing. In this extensive review of how these advances work together to drive digital transformation, this paper synthesizes current research from academic literature with real-world applications of computer technologies from industry. The paper includes discussions regarding the emergence of generative AI and multimodal ML methods, explainable AI, and intelligent automation as new methods to generate better decision-making results and innovations within the business sector. It includes descriptions of multi-cloud/hybrid architectures, serverless computing, edge AI, and fog computing as ways to achieve low-latency scalable infrastructure; and ultimately describes use cases for using IoT with AI-enabled analytic platforms for smart cities; IIoT; and real-time data ecosystems. Cybersecurity subjects discussed in this paper include innovations such as Zero Trust Architecture, AI-based threat detection, and quantum-resistant cryptography. Emerging technology paradigms like blockchain-powered decentralized apps (DApps), Web3 environments, quantum algorithms, AR/VR/MR technologies, and smart robots are examined for potential to change organisations and challenges encountered during their adoption. 'Green computing' strategies are discussed in terms of developing low carbon power systems, creating carbon aware IT systems, and developing sustainable IT practices that reduce environmental impact. This study also explores advances in the fields of human computer interaction, accessibility technology, and ethical governance frameworks, with a focus on society's responsibility to develop inclusive and responsible technological products. The research has revealed multiple challenges that prevent sustainable technology development from progressing, including: scalability; interoperability; regulatory compliance; security threats; digital equity; and adapting to the workforce's new skill sets caused by this shift to sustainable technology. Therefore, developing sustainable technology will require multi-disciplinary co-operation; ethical guidance/path; strategic governance; and continuous innovation in technology development. By combining a technical assessment of IT technology along with a social perspective; an umbrella of knowledge will form to forecast how IT technologies will advance during the period referred to as the era of Intelligent Connected Systems.