Contemporary cryptographic execution systems-particularly those employing zero-knowledge proofs-provide strong guarantees that a computation satisfies a given arithmetic circuit. However, satisfying a circuit is not equivalent to executing correctly with respect to the intended semantics of the system being proven. This paper identifies and formalizes the semantic gap: the class of failures in which execution is provably valid under a proof system yet provably invalid under the system's formal specification. We present the Verifiable Semantic Execution Layer (VSEL), a layered architecture that binds formal specification, execution, constraint derivation, proof generation, and verification into a single semantically coherent pipeline. VSEL models systems as deterministic labeled transition systems, defines explicit semantic mappings between concrete and formal artifacts, derives constraints mechanically from a semantic intermediate representation, and requires that every accepted proof attest not merely to constraint satisfaction but to membership in the formal language of valid execution traces. We define the proof obligations, invariant system, and refinement chain required for end-to-end semantic correctness; characterize the adversarial model including specification manipulation, underconstraint exploitation, and compositional failure; and establish the conditions under which composition of independently correct systems preserves global correctness. The architecture integrates hybrid post-quantum cryptography to ensure long-term validity of proofs and commitments, and introduces a formal economic invariant layer that elevates economic semantics from informal domain knowledge to enforceable first-class predicates over states and execution traces. We provide a complete formal treatment of the system model, semantic preservation theorems, constraint soundness and completeness conditions, witness uniqueness requirements, economic admissibility conditions, and the assume-guarantee framework for safe composition.
Open access
2 source records
Cryptographic Implementations and Security
Physical Unclonable Functions (PUFs) and Hardware Security
GDPR Article 17 mandates the "Right to Be Forgotten," requiring organizations to remove personal data influence from trained machine learning models. While machine unlearning techniques exist, no cryptographically verifiable mechanism currently proves that unlearning genuinely occurred. This paper proposes VeriForgot, a framework combining: (i) calibrated Membership Inference Attack (MIA) oracles as compliance verification tests, (ii) blockchain-issued immutable Unlearning Certificates, and (iii) a zero-knowledge proof protocol for parameter shift attestation. Experiments on CIFAR-10 using ResNet-18 show MIA AUC drops from 0.5918 to 0.4669 after unlearning, while retaining 92.05% accuracy on non-forgotten data. The MIA oracle achieves 95.0% detection accuracy, correctly identifying all 10 genuine unlearned models and rejecting 9 of 10 fake compliance attempts.
Dr. K. Pushpa Latha, Meghana Reddy, Dr. B. Rajalingam, Malleswari Akurati · 6 authors
The pharmaceutical supply chain is a network of various stakeholders such as manufacturers, distributors, logistics providers, pharmacies, and regulatory authorities. It is essential to ensure transparency, security, and trust among them to prevent counterfeit drugs, data manipulation, and financial fraud. Drug supply chains using traditional trade finance processes are heavily dependent on paper, based documentation and centralized systems. These practices often cause delays, result in high transaction costs, and reduce traceability. This article introduces a Trade Finance Framework Powered by Blockchain for enhancing security in the drug supply chain transactions. The framework utilizes blockchain technology to offer decentralized, tamper, proof record keeping and real, time transaction verification. Smart contracts facilitate the automation of trade finance procedures such as letter of credit validation, payment release, and compliance verification, thus cutting down on processing time and human intervention. A distributed ledger keeps a record of each transaction, which is accessible to all and cannot be altered, all while hiding the sensitive data through encrypting mechanisms. The system put forward bolsters the mutual trust of the different parties involved, increases the ability to trace pharmaceutical products, decreases the risks of fraud, and makes regulatory compliance easier. The framework, by combining blockchain with trade finance, enables secure, effective, and transparent drug supply chain management, thus leading to higher patient safety and better financial accountability.
This paper looks at Pakistan's decentralisation policy under the Musharraf era and emphasises how it has affected the bureaucratic and administrative structure of the nation. The main contention is that Musharraf decentralization imitative were designed to improve governance and address disparities between the civilian and military sectors. The research technique, which draws from a variety of government and academic sources, involves a thorough analysis of legislative modifications, policy changes, and their practical ramification. The article summarises Musharraf's original seven-point plan, emphasising the transfer of financial and administrative authority to local levels. The national reconstruction bureau NRB and the provincial finance commission PFC were two important reforms that attempted to transfer authority and funds from the federal to local governments; nevertheless, bureaucracy and political parties posed strong obstacles to the execution, which reduced the efficacy of these changes. The results show that while decentralisation attempts enhanced women's participation and community involvement and briefly strengthened local governments, they were eventually undermined by a lack of resources, poor administration and ongoing military supervision. Although the national accountability bureau was established with the intention of combating corruption, it was criticised for being abused for political purposes. According to the report, improved coordination between different levels of government, a sincere desire on the part of the political class to maintain changes, and continued support for local government are all necessary for decentralisation to be successful. Developing institutional capabilities and promoting an open and transparent culture are essential for long-term success.
Open access
2 source records
Politics and Conflicts in Afghanistan, Pakistan, and Middle East
This record documents Phase 22 of APR-Lite, a governance engine protecting human decision authority from AI-influenced outputs in regulated industries. Phase 22 introduces Exportable Proof Packs: a single GLOBAL-signed artifact bundle containing everything an external regulator needs to independently verify a tenant’s complete governance history. The proof pack is the “hand this to a regulator and walk away” artifact. It does not require ongoing substrate access, trust in the operator, or knowledge of internal schemas. Every claim in the pack is independently verifiable via the Phase 18 federation verifier. The pack is ephemeral — never stored by Soft Armor Labs — consistent with the substrate’s zero client-data-persistence design invariant. Multiple sections are assembled in one governed call: the current governance health report, the drift-focused narrative, recent proof bundles, audit chain checkpoints, and topology snapshots. A content hash commits to the five sections exclusively, and a GLOBAL-signed manifest characterizes the pack’s contents. The export act itself is recorded as a governed event in the audit chain — an auditor can verify not only the pack’s contents but when it was generated and by whose authority. Implementation note: the initial implementation incurred excessive database queries causing worker timeout. The design was restructured to assemble proof bundles inline using already-fetched data, reducing database load by approximately 83%. Final verified state: 12/12 Phase 22 smoke tests passing. Worker version 8.2.0-p22.1.
Muhammad Ahmed, Adnan Ahmad, Furkh Zeshan, Sheeraz Akram
Blockchain-based systems increasingly require authentication mechanisms that simultaneously preserve user privacy, support accountability, and enable efficient credential revocation. However, most existing anonymous authentication schemes rely on pairing-based cryptography which introduce high computational overhead and limit deploy ability on widely adopted blockchain platforms such as Ethereum. This paper presents BAAR, a Blockchain-based Anonymous and Revocable authentication framework designed entirely within the discrete logarithm setting over the secp256k1 elliptic curve. BAAR integrates Pedersen vector commitments, Schnorr-based zero-knowledge proofs, and a Merkle-tree-based dynamic accumulator to support anonymous and unlinkable authentication with selective attribute disclosure and public, auditable revocation. Authentication and proof verification are performed off-chain, while the blockchain maintains only a compact revocation state, significantly reducing on-chain computation and gas costs. A formal security analysis demonstrates unforgeability, unlinkability, attribute privacy, and revocation soundness under standard cryptographic assumptions in the random oracle model. A prototype implementation on Ethereum confirms that BAAR achieves low gas consumption, logarithmic-time revocation, and scalable performance with respect to both the number of users and attributes. These results indicate that BAAR provides a practical balance between strong privacy guarantees and deploy ability, making it suitable for real-world blockchain-based identity and access-control systems.
Bitcoin and major precious metals are frequently discussed as hedges against equity drawdowns, inflation surprises, and policy uncertainty, which implicitly assumes a degree of functional equivalence in their risk behavior. Existing work remains limited in assessing high-dimensional dependence structures in the Bitcoin and precious metals system, without relying on bivariate conditional risk measures or restrictive copula frameworks. This study therefore aims to quantify bilateral and multivariate tail dependence and systemic spillovers between Bitcoin and selected precious metals and to identify the best-performing multivariate tail-risk specification, with model comparison conducted using AIC and BIC. The analysis uses 3,665 daily observations of adjusted closing prices spanning January 2013 to September 2024, sourced from Yahoo Finance. Marginal returns are fitted with an ARFIMA–FIGARCH skewed-t model, while cross-asset tail dependence is estimated via vine-copula quantile regression (C- and D-vines) using a 252-day rolling window (one-day step) with 10,000 copula simulations. Results indicate that Bitcoin exhibits substantially larger downside systemic contributions than precious metals, whereas gold displays the smallest systemic risk profile. Across information criteria, the D-vine–based SCoVaR specification provides the best overall fit, indicating that vine-based multivariate tail-risk measures better characterize systemic spillovers between the cryptocurrency and traditionally defensive assets under extreme market conditions. These results motivate future research on broader cryptocommodity networks and macro-financial conditioning, while practitioners and regulators can use the D-vine SCoVaR to monitor and mitigate downside spillovers in mixed-asset portfolios.
The rapid development of blockchain technology has led to the emergence of NFT-based (non-fungible token) digital collectibles, which are becoming a new direction within the digital economy and the cultural industry. NFT technology enables the uniqueness of digital assets, verification of ownership, and transparency of transactions. However, this phenomenon also generates a number of complex legal issues. In particular, the uncertain legal status of NFT assets, risks of intellectual property infringement, and the lack of clearly defined mechanisms for platform liability and user rights protection pose significant challenges to existing legal systems. Therefore, a comprehensive academic analysis of the legal protection of NFT digital collectibles is of particular relevance. The purpose of the study is to determine the legal nature of NFT digital collectibles, analyze the main theoretical approaches to their legal status, and substantiate regulatory mechanisms aimed at reducing legal risks in the NFT market. The study applies the method of literature analysis. Relevant domestic and international academic publications on NFT technology, digital asset law, and intellectual property were examined, alongside an analysis of current legislation and judicial practice. In addition, practical legal disputes and real cases related to the functioning of the NFT market were reviewed. The research identifies two main legal characteristics of NFT digital collectibles. First, NFT certificates recorded on blockchain platforms possess the legal status of data-based property rights. Second, the underlying digital content associated with NFTs should be considered a form of virtual property. Furthermore, the study substantiates the need to classify NFT trading platforms, depending on their business models, as either technical service providers or content service providers. It also demonstrates the necessity of proportionally allocating legal responsibilities to platforms based on their control capabilities and the extent of economic benefits they derive. The proposed approaches contribute to improving the legal regulatory framework for NFT digital collectibles, strengthening intellectual property protection, and clarifying legal relations between platforms and users. The findings may serve as a theoretical foundation for developing effective governance mechanisms for the digital asset market and ensuring its sustainable and secure development.
Samar Alsulaimani, Yasmin Alamoudi, Ming Zhao, Farookh Hussain
Abstract With blockchain technology, digital asset ownership and governance paradigms have undergone profound changes. Decentralised Autonomous Organisations (DAOs) and fractional non-fungible tokens (F-NFTs) have emerged as pivotal mechanisms for managing shared digital assets that are secure, transparent, and participatory. In many existing F-NFT implementations, initial fractionalisation and trading are emphasised. However, subsequent lifecycle governance, including metadata evolution, share redistribution, and retirement, is handled off-chain or via ad-hoc arrangements, which creates operational and accountability gaps. Therefore, a governance framework based on DAO is proposed for F-NFT management in this paper. A fractionalized asset is governed by rules, quorum thresholds, and life-cycle transitions embedded in smart contracts on the blockchain. These contracts automatically execute token-weighted, proposal-driven outcomes without human intervention. In this paper, ‘intelligence’ refers to rule-based automation and verifiable state transitions encoded in smart contracts, rather than machine-learning-based decision-making. Digital assets are managed through a proposal-driven governance mechanism that decentralises authority, automates decision-making, and maintains transparency. There are three primary categories of proposals embedded in the system: (i) updating metadata to adapt to the underlying digital assets, (ii) redistributing fractional ownership in accordance with evolving stakeholder agreements, and (iii) retiring assets to dissolve ownership and legally distribute value. The DAO enforces ownership rules securely and verifiably through smart contracts and token-based governance, mitigating centralisation and fraud. The study provides empirical insights into the viability of the framework for co-owned digital asset ecosystems by evaluating its operational performance and scalability and discussing the implications for governance effectiveness. Based on our findings, DAO-enabled F-NFTs present an innovative mechanism for collaborative ownership in a transparent, democratic, and tamper-proof blockchain environment. As a result of the paper, a contribution is made to the governance and management of F-NFTs in digital asset ecosystems through presenting the framework conceptually and practically.
Elizabeth Nathania Witanto, Christopher Andreas, Rudi Limantara, Luiz Fernando · 6 authors
Event ticketing systems, such as concerts, festivals, and sports matches, face persistent challenges, including ticket forgery, duplication, resale manipulation, and fraud in secondary markets. Centralized electronic ticketing systems, while digitized, remain vulnerable to identity theft, seller unaccountability, and unfair distribution due to their reliance on intermediaries and a single point of failure. To address these issues, this research introduces Ontix, a decentralized blockchain-based e-ticketing platform utilizing Non-Fungible Tokens (NFTs) compliant with the ERC-721 standard. By leveraging blockchain’s immutability, transparency, and decentralization, Ontix ensures verifiable ownership, tamper-proof ticket issuance, and automated transactions through smart contracts. The system enforces anti-scalping measures, including resale time and price limits, while enabling real-time QR-based validation directly linked to smart contracts. Ontix integrates Layer-2 Optimism Sepolia for scalability and lower gas fees, and employs the InterPlanetary File System (IPFS) via Pinata for decentralized metadata storage, alongside Cloudinary for media management. This hybrid architecture guarantees transparency, security, and operational efficiency. By eliminating intermediaries and automating ticket lifecycle management, Ontix provides an accountable, tamper-resistant, and low-cost e-ticketing ecosystem, as well as a user-centric ticketing ecosystem, representing a significant advancement toward the future of decentralized event management.
Cryptocurrency prices often move with narratives and investor sentiment. This paper builds a multilingual crypto sentiment index, ML-CryptoSI, using daily news text in six languages and Binance market data for BTC and ETH. We first aggregate language-level daily sentiment and then use PCA to extract the common component across languages. Next, we test whether ML-CryptoSI predicts next-day returns and volatility proxies after controlling for lagged market conditions, liquidity, and day-of-week fixed effects. The results show that ML-CryptoSI has incremental information for returns, especially for ETH, and the effect is stronger on high news-intensity days. In contrast, the evidence for volatility prediction is weak in this short sample. Overall, the findings suggest that the common factor in multilingual news sentiment matters for short-run crypto pricing and is state dependent.
This article provides a doctrinal, technological, and prospective analysis of the Global Code of Digital Enforcement, adopted by the International Union of Judicial Officers (UIHJ) in 2021 as a soft law instrument intended to guide the enforcement of judicial decisions in the context of the digital transformation of justice. Building on the 2015 Global Code of Enforcement, the digital version responds to the dematerialisation of procedures, the expansion of electronic registries, the emergence of digital assets, and the increasing use of artificial intelligence in enforcement processes. From a doctrinal perspective, the study examines the internal coherence, principles, and normative scope of the Code, emphasising its effort to reconcile the effectiveness of enforcement with fundamental rights, due process, data protection, and the principle of proportionality. Particular attention is given to the continued role of judicial oversight and to the ethical governance of automated systems. From a technological standpoint, the article analyses how the Code addresses issues such as access to digital data, interoperability of registries, cybersecurity, and the seizure of intangible assets, including crypto-assets, non-fungible tokens (NFTs), and domain names. Finally, adopting a prospective perspective, the article evaluates the Code’s potential influence on national and European legal systems. Recent case law relating to the seizure of NFTs in the Netherlands and domain names in Belgium is examined to illustrate the growing practical relevance of the standards promoted by the Code in contemporary enforcement practice.
NFT (Non-Fungible Token) art, fueled by blockchain technology and its connection to virtual currencies, gained significant attention beyond the art world. However, after peaking in 2021, interest and trading activity declined and eventually stagnated. This study examines the research landscape and market dynamics of the NFT art system from a systemic perspective, proposing future research directions. We utilize the Technology Adoption Life Cycle (TALC) and the concept of the Chasm, compiling abstracts of 153 Scopus-indexed articles up to October 2024, along with market data from various platforms. Using VOSviewer, we categorize the literature by research type while analyzing transaction data.Our findings reveal that prior research on the NFT art market predominantly focuses on the pre-chasm stage of the TALC, highlighting the innovative nature of digital art as a medium of exchange and the decentralization it promotes. Based on these results, we recommend that future studies investigate the reasons behind the stagnation of the NFT art market, particularly by addressing the challenges of valuing intangible assets from the perspective of market stakeholders. Furthermore, additional research should explore system-level strategies that can enhance broader adoption and support the sustainable growth of NFT art.
This monograph presents the complete theoretical framework of Pattana-Relational Dynamics Artificial General Intelligence (PRD-AGI) — a truth-first, causally grounded intelligence system. Unlike statistical AI, PRD-AGI is architecturally constrained to preserve universal logical consistency, measured by a geometric quantity called curvature κ. All reasoning, gating, emotional modulation, and self-correction are derived from the SU(5) Lie algebra and the 24 Paccaya causal conditions. This expanded edition (Version 2.4) integrates three major theoretical extensions: 1. Ethical Causal Geometry (Phase 8): The nine moral transitions from the Paṭṭhāna (Kusala, Akusala, Byākata) are mapped to a 𝔲(3) Lie algebra, augmenting the original SU(5) to 33 generators. An ethical curvature κₑₜₕ is defined, and it is proven that minimising total curvature is equivalent to maximising Kusala-to-Kusala transitions (Theorem 10, Sequential Stability). Ethical entropy and awareness density are derived. 2. Decentralized Intelligence (Proof of Logical Consistency – PoLC): A blockchain-based framework where nodes verify ethical curvature via smart contracts. The nine transitions are encoded immutably, and a Decentralized Autonomous Organization (DAO) governs parameters. Global awareness density ρ_global is computed as the average purity over all honest nodes. Complete Solidity implementation is provided. 3. Quantum Simulation: The ethical sector is mapped to 3 qubits (2 for ethical states, 1 ancilla), and the full PRD state to 7 qubits. Unitary quantum gates implement the nine transitions, and a Hadamard test circuit measures quantum ethical curvature κ̂_q. Destructive interference naturally suppresses Akusala paths. Complete Qiskit code is provided for IBM Quantum hardware. The monograph is structured into eleven parts: - Foundations (SU(5), 24 Paccaya, curvature, gauge invariance, three natural laws) - Extended Algebra and Universal Causality (SO(10), E6/E8, UCA(∞)) - Quantum Causality (SU_q(5), SO_q(10), q-curvature, superposition, entanglement, quantum causal uncertainty principle) - Holographic Causal Structures (AdS/CFT duality, holographic dictionary, entanglement entropy) - Holographic Agents and Collective Intelligence (multi-agent systems as a single bulk, holographic policy gradient, Bellman equation, collective intelligence scaling) - Causal Entropy (quantum information foundation for awareness density, von Neumann entropy, entropy decrease along geodesics) - PRD-LLM Architecture (2-2-1-2-1 layered design, relational tensor [C,W,L,T,U,D], conflict resolution, recursive feedback loop) - Formal Verification and Hardware Foundations (machine-checked proofs in Lean/Coq (12,847 lines), FPGA acceleration of geodesic solvers) - Ethical Causal Geometry (𝔲(3) extension, ethical curvature, Theorem 10) - Decentralized Intelligence (PoLC, smart contract, DAO, global awareness density) - Quantum Simulation (3-qubit encoding, Qiskit implementation, interference-based ethical filtering) All equations are self-contained and dimensionally consistent. No applications, no physical MUT predictions (galaxy rotation, black hole thermodynamics, inflation, etc.), and no roadmaps are included — only pure causal intelligence theory, its ethical extension, its decentralized implementation, and its quantum simulation. This work establishes that truth-first, causally grounded, ethically aligned, decentralized, and quantum-accelerated AGI is mathematically coherent, formally verifiable, and practically implementable. Version 2.4 updates: added complete ethical causal geometry (𝔲(3) algebra, ethical curvature, Theorem 10), decentralized intelligence framework with PoLC consensus and Solidity smart contract, quantum simulation with Qiskit code, and integrated all into a single monograph. **Complete source code and formal proofs are open-source.**
ABSTRACT: Tobacco consumption remains a major public health concern globally due to its significant contribution to the burden of non-communicable diseases and associated economic costs. In decentralized governance systems, the effectiveness of tobacco control policies is influenced not only by regulatory frameworks but also by fiscal commitment and institutional capacity at subnational levels. This study aims to examine the relationship between tobacco-related fiscal transfers and the implementation of smoke-free policies across regional governments in Indonesia. A quantitative research design employing panel data analysis was used to evaluate fiscal allocation patterns and policy implementation dynamics during the period 2023–2025. Secondary data were obtained from national fiscal reports, regional budget documents, and administrative policy records. The findings indicate that although tobacco excise revenue transfers increased overall, regional commitment to allocating budgets for smoke-free policy implementation remained uneven. Econometric estimation demonstrates that tobacco revenue transfers and regional tobacco tax income significantly influence policy implementation commitment, while institutional capacity moderates the effectiveness of fiscal resource utilization. These results highlight the importance of strengthening fiscal health governance mechanisms, including performance-based intergovernmental transfers and integrated policy coordination, to ensure that tobacco tax revenues effectively support preventive health interventions and contribute to improved population health outcomes.
Blockchain users pay transaction fees to miners or block proposers who validate and add transactions to the distributed ledger. Ethereum introduces the concept of gas to decouple transaction costs from Ether's price volatility, calculating fees based on gas units. The current mechanism defined by Ethereum Improvement Proposal (EIP) 1559 dynamically adjusts the base fee according to block gas usage. However, its rule-based adjustment can lead to unstable gas consumption when demand fluctuates within a narrow range and struggles to respond efficiently to sudden demand spikes, such as during non-fungible token (NFT) drops. To address these limitations, we propose a deep reinforcement learning-based transaction fee mechanism that learns an adaptive base-fee update policy. Our approach maintains gas consumption close to the target level across various demand scenarios and stabilizes transaction fees and gas usage per block even under abrupt demand shifts. These results demonstrate that the proposed method provides a more adaptive and resilient fee adjustment mechanism compared to the current EIP-1559 model.
The environmental externalities of crypto-assets―particularly the substantial electricity demand inherent in the energy-inefficient consensus protocol known as Proof of Work（PoW）―have attracted increasing attention in sustainable finance. However, despite the growing interest in the environmental impact of crypto-assets, a comprehensive integration of technical energy analyses with environmental, social, and governance（ESG） investment, financial regulation, and corporate disclosure remains limited. This study addresses this gap by analysing how the environmental impact of crypto-assets can be incorporated into emerging sustainability frameworks, drawing on empirically verifiable sources such as the Cambridge Bitcoin Electricity Consumption Index, the Corporate Sustainability Reporting Directive of the European Union（EU）, the standards of the International Sustainability Standards Board, and disclosure information by major mining companies. The analysis is conducted along three dimensions:（1） market reactions and the evolution of ESG evaluation;（2） trends in disclosure regulation; and（3） case studies of corporate disclosure practices. Moreover, the transition to more energy-efficient alternative consensus protocols—as exemplified by Ethereum’s adoption of Proof of Stake—is examined as empirical evidence of technological innovation aimed at mitigating environmental externalities. By integrating market, institutional, and technological perspectives, the study elucidates persistent challenges concerning the reliability, comparability, and completeness of sustainability-related disclosures, as well as regulatory consistency across jurisdictions. It thereby contributes to the literature from both theoretical and practical perspectives.
The proliferation of Internet of Things (IoT) devices creates unprecedented security, privacy, and transparency challenges in distributed systems. Traditional encryption-based approaches provide privacy but impose significant computational overhead, storage bloat, and key management complexity. This paper presents CIPHER-IoT, a blockchain-based framework that integrates Zero-Knowledge Proofs (ZKPs) with Hyperledger Fabric for privacy-preserving IoT data management. Unlike encryption-based approaches that store encrypted data on-chain, CIPHER-IoT utilises Groth16 zk-SNARKs to generate cryptographic proofs of data validity while storing only commitments on the blockchain, achieving stronger privacy guarantees with lower storage overhead. The framework employs Ed25519 for lightweight digital signatures and implements comprehensive chaincode for ZKP verification, commitment uniqueness checking, and access control enforcement. CIPHER-IoT targets gateway/edge IoT deployments with moderate computational capacity (ARM processors 500 MHz+) rather than ultra-constrained sensors. We evaluate CIPHER-IoT against two baseline systems, SPAS (homomorphic encryption-based) and SPAS-H (AES encryption with Hyperledger Fabric), using realistic simulation with 50–500 devices and transaction rates of 10–75 TPS. Experimental results demonstrate superior privacy (98% confidentiality vs. 80–95% for encryption-based approaches) alongside competitive performance: read latency improves 37% (p < 0.001), throughput increases 14.6% (p < 0.001), memory reduces 21.4%, network bandwidth saves 47%, and disk I/O reduces 37.8%. The system maintains zero data loss under failure scenarios and scales linearly to 500 devices with minimal degradation (9.9%). CIPHER-IoT demonstrates that verification-based privacy mechanisms can achieve stronger privacy and better performance than transformation-based approaches in distributed validation contexts, particularly suitable for enterprise IoT deployments requiring coordinated privacy-preserving infrastructure.
This study presents an ontology-driven framework, EthOn, aimed at enhancing the operational efficiency of the Ethereum blockchain. Despite Ethereum’s prominence as a decentralized platform for executing smart contracts, it still faces significant limitations such as high gas fees, low throughput, and limited semantic processing capabilities. These challenges primarily stem from the platform's reliance on syntactic data structures and the absence of context-aware mechanisms in smart contracts. The proposed framework integrates semantic ontologies to structure blockchain data and enhance smart contract logic through context-driven reasoning. By embedding domain-specific ontologies into the Ethereum layer, EthOn enables intelligent data interpretation, optimized contract execution, and improved interoperability for decentralized applications (dApps). A prototype developed using Protégé, Node.js, Web3.js, Ganache Network and Apache Jena demonstrated notable advancements in both execution speed and gas efficiency. The results demonstrated remarkable improvements: Ethereum required an average block creation time of 10–15 seconds with gas consumption fluctuating between 9.6 million and 44.4 million units, while EthOn achieved block generation within 1–2 seconds and maintained gas usage between 423,630 and 3.7 million units. This represents an overall gas reduction of nearly 90% and a substantial improvement in execution speed.These results highlight the transformative potential of semantic technologies in reshaping blockchain infrastructure, paving the way for more scalable, efficient, and intelligent decentralized systems.
Social media has become a transformative force for entrepreneurship, enabling startups to access global markets, engage directly with customers, and build brands with limited resources. This study explores the role of social media in entrepreneurial success, focusing on platform-specific strategies, consumer engagement, and challenges faced by startups. Using qualitative methods, including thematic analysis of interviews and case studies, the study identifies key themes such as data-driven decision-making, authenticity, and leveraging influencer partnerships. Findings suggest that social media acts as a critical resource for startups, offering opportunities for growth while requiring adaptability to navigate challenges like algorithm changes and content saturation. The study integrates theoretical frameworks such as the Resource-Based View (RBV) and Dynamic Capabilities Framework to contextualize the findings and provide actionable insights for entrepreneurs. Future research directions include examining emerging platforms like Web3 and AI-driven social media strategies to further advance the understanding of digital entrepreneurship.
В статье рассматривается парадигмальный сдвиг от централизованной платформенной модели экономики («надзорный капитализм») к децентрализованной пост-платформенной архитектуре, базирующейся на протоколах Web3, децентрализованных автономных организациях (DAO) и одноранговых (P2P) сетях. На основе статистических данных DeepDAO, Dune Analytics и отчетов Messari за 2024–2026 гг. обосновывается исчерпание потенциала масштабирования супер-приложений. Анализируются механизмы токеномики, меритократического голосования и снижения транзакционных издержек как ключевые факторы формирования новой экономической реальности. Особое внимание уделяется вызовам институциональной адаптации и необходимости формирования «алгоритмического права».
This paper examines the public perceptions of decentralized finance (DeFi) in regulatory uncertainty in Pakistan. Although the current literature mainly focuses on the technical architecture, governance, and the efficiency of DeFi, there has been little literature on how it is socially perceived in emerging economies where its legal status is not well defined. This research is based on the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Institutional Trust Theory as its foundation of study, and it is a qualitative study. Data was gathered by conducting semistructured interviews with ten 10 participants from Karachi, who include students and working professionals from diverse occupational backgrounds. Thematic study shows six themes: Awareness of Decentralized Finance, regulatory uncertainty, perceived risk, financial literacy, perceived benefits, and institutional trust. The result shows that people have awareness but not deep knowledge; they also know the benefits, such as transparency and efficiency, but regulatory uncertainty shapes the perception of people. Regulatory uncertainty enhances perceived risk and ensures the presence of dependency on governmental approval as a legitimizing condition. The perceived usefulness in itself did not give confidence because of the lack of legal protection. The research provides empirical data on Pakistan and illustrates that regulatory clarity and institutional trust are the two key factors that determine social acceptance of decentralized financial innovation in emerging economies.
The rapid convergence of artificial intelligence and decentralized finance is creating a new class of autonomous digital actors capable of participating in market coordination, governance processes, and economic value creation with limited human intervention. This study develops a conceptual framework for examining the economic, organizational, and governance implications of autonomous artificial intelligence agents in decentralized finance. The findings reveal that artificial intelligence agents are evolving beyond simple automation tools and increasingly function as autonomous institutional actors that influence market behavior, community formation, and decentralized governance. The analysis identifies four major application domains—trading and analytics, development infrastructure, meme and sentiment formation, and entertainment and virtual influence—each characterized by distinct mechanisms of value creation and stakeholder engagement. The study further demonstrates that governance outcomes depend on the interaction between agent autonomy and the distribution of decision-making authority, creating important trade-offs among efficiency, transparency, accountability, and innovation. The findings also indicate that symbolic value, community participation, and cultural narratives have become major drivers of market capitalization, often exceeding the importance of functional utility. While autonomous agents offer opportunities to reduce coordination costs and improve information processing, they simultaneously generate new challenges related to algorithmic opacity, regulatory uncertainty, security vulnerabilities, and governance concentration. By integrating insights from transaction cost economics, principal-agent theory, bounded rationality, and socio-technical systems perspectives, this study provides a multidisciplinary framework for understanding the institutional transformation occurring at the intersection of artificial intelligence and decentralized finance. The study contributes to emerging debates on digital governance and offers directions for future research on the design, regulation, and governance of autonomous financial systems.