R Udayakumar, A Haja Alaudeen, Anjali Goswami, N Arvinth · 5 authors
Blockchain technologies incorporated with decentralized energy grids can offer new paradigms in energy management, distribution, and consumption. Trust building among participants in decentralized energy systems is a critical challenge in the absence of a central authority. Foremost, the self-executing, fully autonomous blockchain-based smart contracts and the decentralized automated systems enable real-time, secure, and transparent business transactions. This paper examines the domain of smart blockchain contracts in decentralized energy grids. Smart contracts facilitate self-enforcement, aiding trust-building. Invoice blockchain contracts enable automated energy exchange, thereby facilitating contract execution without third-party involvement. Trust-building, system decentralization, energy producers and consumers bypassing operators, and operational cost reduction for self-sustainability provide system autonomy. The paper also discusses self-governing blockchain contract systems engineering. In smart energy contracts, the paper outlines system challenges, which include load, interoperable infrastructure, and energy consumption. Empirical and case study research, which are the primary focus of the paper, present blockchain contracts for decentralized energy systems as a trust-management and transaction-integration technology.
The article examines the role of cryptocurrencies in the shadow economy, their specific features that create conditions for illegal financial transactions. The methods of using digital assets in criminal activities, including money laundering and illegal transactions, are analyzed. Special attention is paid to the problems of regulating the cryptocurrency market in Russia, new legislative initiatives and control measures. Technologies for monitoring blockchain transactions aimed at detecting suspicious transactions and reducing the risks of using cryptocurrencies in criminal schemes are also affected.
Romulo de Moraes, Arthur G. Bubolz, Denner Ayres, Vinícius Teixeira Pinto · 5 authors
Este artigo apresenta uma arquitetura para loterias descentralizadas na rede Ethereum, baseada em contratos inteligentes, aleatoriedade verificável e otimização de armazenamento por meio de Merkle Tree. A proposta visa reduzir o custo médio das transações (gas fees) e aprimorar a escalabilidade onchain, comparando três abordagens distintas de armazenamento: array, mapping e Merkle Tree. Os resultados mostram que o consumo de gas evidencia uma vantagem expressiva da Merkle Tree, reduzindo em até três ordens de magnitude o custo total, o que confirma sua eficiência e potencial para aplicações descentralizadas de alta demanda.
Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive that enables a prover to convince a verifier that something is true without leaking the private witness. Current zkSNARKs face significant computational costs in generating proofs, which restricts their use in areas like private payments, confidential smart contracts, and anonymous credentials. Private delegation offers a practical solution by outsourcing the heavy computation to powerful external workers without leaking any private information. In this work, we propose HyperSiniel, an efficient private delegation framework for general zkSNARKs that achieves a new feature called guaranteed output delivery (GOD). HyperSiniel is designed to be compatible with any universal zkSNARKs constructed from a polynomial interactive oracle proof (PIOP) and a polynomial commitment scheme (PCS). It enables a computationally limited delegator to outsource proof generation to several workers in a fully non-interactive and privacy-preserving manner. Compared to the most state-of-the-art frameworks (e.g., Siniel [NDSS'25]), HyperSiniel ensures that the delegator always receives a correct proof, regardless of malicious worker behavior. We implement HyperSiniel and compare the performance with Siniel across varying bandwidths and circuit sizes. Under low-bandwidth conditions (10MBps), HyperSiniel incurs only an additional 25% overhead compared with Siniel, while the total running time of HyperSiniel is almost identical to Siniel under high-bandwidth settings (1000MBps). These results show that the strong robustness guarantee of GOD in HyperSiniel comes almost for free, making it a practical and secure solution for real-world zkSNARK delegation.
Open access
Cryptography and Data Security
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
André Augusto, Rafael Belchior, Jonas Pfannschmidt, André Vasconcelos · 5 authors
Cross-chain bridges are a blockchain interoperability middleware that supports the transfer of assets and data across blockchains. However, several of these bridges have vulnerabilities that have caused 3.2 billion dollars in losses since May 2021. Some studies have revealed the existence of these vulnerabilities, but there is little quantitative research available, and there are no safeguard mechanisms to protect bridges from such attacks. Furthermore, no studies are available on the practices of cross-chain bridges that can cause financial losses. We propose XChainWatcher (Cross-Chain Watcher), a modular and extensible logic-driven anomaly detector for cross-chain bridges. It operates in three main phases: (1) decoding events and transactions from multiple blockchains, (2) building logic relations from the extracted data, and (3) evaluating these relations against a set of detection rules. Using XChainWatcher, we analyze data from two previously attacked bridges: the Ronin and Nomad bridges. XChainWatcher successfully identified the transactions that led to losses of $611M and $190M (USD) and surpassed the results obtained by a reputable security firm in the latter. We not only uncover successful attacks, but also reveal other anomalies, such as 37 cross-chain transactions (cctx) that should not have accepted, failed attempts to exploit Nomad, over $7.8M worth of tokens locked on one chain but never released on Ethereum, and $200K lost by users due to inadequate interaction with bridges. We provide the first open dataset of 81,000 cctxs across three blockchains, capturing more than $4.2B in token transfers.
Saudi Arabia’s rapid urbanization driven by Vision 2030 demands sustainable municipal finance systems. Using a mixed-methods analysis, this study analyzes 360 expert perspectives and identifies the key challenges of fiscal centralization (β = –0.14), governance deficits (20.2% variance), and overreliance on centralized funding (31.8% variance). However, decentralization (β = 0.31), policy alignment with Vision 2030, and green finance tools emerge as transformative pathways. Regression and correlation analyses reveal that municipal autonomy and legal frameworks are crucial in promoting sustainability integration. This study advocates for fiscal decentralization, Sharia-compliant green bonds, and institutional reforms and offers useful insights for policymakers.
Abstract The accelerating dominance of non-human agents in digital infrastructures has created an existential imbalance between human intentionality and synthetic computation. All identity-centric and post-hoc verification paradigms have failed against advanced automation. This work introduces Proof of Being (PoB) — an ontological cryptographic primitive that binds digital agency to continuous, embodied human presence without revealing identity. Using Human Intention Semantic Proof Units (HISPU) — the fusion of physiological dynamics, semantic activity structure, and changing environmental context — we generate zero-knowledge proofs of authentic human engagement. From this substrate emerges the Vital Presence Token (VPT), a new energy-like digital asset that supplies “existential energy” exclusively to human-authorized agents. Ontological Digital Agents Management (ODAM) implements a biological-immune-system analogue: agents lacking fresh VPT undergo ontological death and cannot claim computational resources. The framework establishes verifiable human presence as the constitutional substrate for post-AGI digital civilization and defines the economic foundations of Web4. Keywords: proof of being, ontological cryptography, human presence verification, digital immune system, vital presence token, Web4, post-AGI governance, zero-knowledge biometrics, existential energy, digital agents management, human-in-the-loop, semantic intentionality, biological computing, HLA/MHC analogy, human sovereignty, scarcity, decentralized identity, ODAM, HISPU.
Martin Christy ABIAYA'A, Tati Gaelle TIMBA, Jean Hugues NLOM, Marcellin NDONG NTAH
Abstract The objective of this article is to analyze the effect of fiscal decentralization on early childhood education in Cameroon. Using a methodological framework based on econometric modeling by ordinary least squares (OLS), generalized least squares (GLS), and the generalized method of moments (GMM), it emerges that fiscal decentralization positively and significantly affects early childhood education in Cameroon. The results obtained by OLS and GLS reveal that Fiscal decentralization has a significant and positive effect on the number of desks per student. The Global Monitoring Mechanisms (GMM) demonstrate that fiscal decentralization leads to a significant and positive increase in both the number of classrooms per student and the number of desks per student. The investigations revealed that fiscal decentralization has a positive effect on early childhood education in Cameroon.These results suggest implementing financing mechanisms for local authorities to stimulate local development through the provision of sustainable socioeconomic infrastructure that can ensure equal and equitable access to education for children. Keywords: Cameroon, schooling, early childhood, fiscal decentralization
Abstract - The paper referenced proposes a decentralized marketplace model for trading, verifying, and managing the ownership of AI models by means of blockchain and NFTs. Given the need for trusted exchange and provenance in the management of AI assets, the authors propose a system wherein AI models and datasets are represented as NFTs on a public blockchain, providing transparent, traceable, and secure transactions. Smart contracts automate auctions, royalty distributions, and ownership transfers. Further security and privacy are provided by TEEs, proxy re-encryption, and decentralized storage (IPFS). Collaboration is enabled through the architecture, which allows contributors to improve and resell models, while royalty schemes guarantee fair compensation for creators. Details of the implementation include smart contracts in Solidity and cost analyses for transaction efficiency. Evaluation in terms of security is resilient against Sybil and Eclipse threats. It is also set up as broadly adaptable to both public and private AI assets and easily generalizable to other situations of digital assets to ensure robust provenance, fair remuneration, and trustless exchange. Key Words: Blockchain, Non-Fungible Tokens(NFTs), Decentralized AI marketplace, Smart Contracts, Digital Ownership
National identity systems require efficient, equitable decision-making that safeguards personal data. This article proposes a Self-Sovereign Identity (SSI) architecture, supported by a Verify-Without-Reveal (VWR) framework, designed for national-scale implementation. SSI places credentials in a citizen wallet and enables selective disclosure and zero-knowledge proofs, so services can verify attributes without seeing underlying records. VWR adds the policy and accountability spine: yes/no attribute APIs for holder-absent cases, purpose-bound and zero-trust enforcement on every call, and an immutable audit layer on a permissioned ledger. The study synthesises current standards and leading implementations in Europe and worldwide and formulates a deployable blueprint with clear roles, consent and lawful-override flows, per-agency pseudonyms, and regulator and citizen visibility. The study outlines reference APIs, user experiences for wallets and verifiers, and performance metrics suited for national workloads. Privacy-preserving AI strengthens biometric liveness, fraud detection, and anomaly response without centralising sensitive data. The framework aligns with GDPR data minimisation and purpose limitation, supports the European Digital Identity Wallet, and meets high-risk AI governance requirements. Results show how SSI proofs and VWR controls reduce unconsented disclosure and cross-agency browsing, while keeping latency low and interoperability high. The contribution is both conceptual and operational: a phased migration path that turns verify-without-reveal into the default mode for government and regulated services, improving security, inclusion, and public trust.
The digital transformation of education necessitates secure, private, and learner-centric methods for verifying academic credentials. Conventional verification processes expose sensitive personally identifiable information, creating privacy risks that conflict with data protection regulations like GDPR. Existing blockchain solutions for educational credential verification face persistent challenges including prohibitive transaction costs, privacy vulnerabilities, and inflexible verification models. This paper presents VeriZKP, a proof-of-concept architecture demonstrating gas-free credential verification on Ethereum using zero-knowledge proofs. The core innovation lies in separating on-chain trust anchoring from off-chain cryptographic computation, enabling a novel cost-elimination mechanism. The system leverages Ethereum’s view functions through pre-compiled verifier contracts to achieve zero gas consumption for verification operations while preserving privacy through selective disclosure mechanisms. Our prototype, evaluated on Ethereum Sepolia testnet, validates the fundamental feasibility of this approach. Results demonstrate complete elimination of verification costs, practical client-side proof generation times of 1.02-1.63 seconds on standard hardware, and support for multi-attribute credential verification. The architecture proves both economically viable and performant for blockchain-based identity systems.
Reaching consensus in Proof-of-Stake (PoS) based consensus protocols, requires supermajority agreement among participating validator nodes. Such protocols need significant network resources due to the concurrent voting of a large number of consensus nodes. As a solution, these nodes are divided into committees, with each committee voting individually at a dedicated time slot. In this paper, we introduce CliqueSensus, a protocol that, given a distribution of consensus nodes into committees, lets them self-organize into small, ephemeral clusters structured in clique topologies, to accelerate the voting process, while using only a small fraction of the network resources required by conventional message dissemination methods. Our evaluation demonstrates that our protocol exhibits rapid convergence and operates with minimal network overhead. We focus on the PoS consensus algorithm adopted by Ethereum 2.0. In addition to our protocol, we also analyze and simulate the clustering approach that Ethereum has adopted, showcasing that our protocol can reduce validation message dissemination time by 23% to 70%, while requiring about 190 times fewer validation message forwards.
Serverless computing promises on-demand elasticity and simplified deployment, yet today's production-grade serverless platforms remain tied to a single-provider, centrally scheduled control plane. This centralized scheduling model faces mounting challenges in handling heterogeneous policies, data governance constraints, and dynamic workloads for the modern web, where applications increasingly span multiple geo-distributed autonomous administrative domains. In this paper, we present Mocha, a decentralized, policy-aware framework for scheduling serverless functions across a federated ecosystem. At its core, Mocha proposes a hierarchically structured distributed hash table that embeds geographical and organizational context to facilitate locality-aware scheduling without any central authority. By implementing a formally specified compliance engine at each domain, Mocha guarantees that all regulatory, locality, and resource constraints are honored for function placement decisions. Experiments show that Mocha reduces scheduling tail latency by 4–9× compared to alternatives while maintaining full policy adherence.
Matthieu Pigaglio, Onur Ascigil, Michał Król, Felix Lange · 9 authors
Layer-2 protocols such as rollups can help address Ethereum's throughput limits. An efficient data availability layer is key for layer-2 support in Ethereum, but broadcast methods do not scale. A promising approach is the selective distribution of layer-2 data and its verification by data availability sampling (DAS). Integrating DAS with Ethereum consensus is, however, a challenge, as data must be shared and sampled within 4 seconds of each consensus slot.
This paper presents a model in which risk-averse individuals can purchase insurance via traditional indemnity contracts or Decentralized Finance (DeFi) smart contract-based instruments. The model incorporates key features of DeFi insurance, including parametric payouts, basis risk arising from imperfect loss verification and pooled collateralization involving the risk of liquidity shortfalls. We characterize optimal insurance choices as a function of pricing, payout correlation and risk preferences. Numerical results show that DeFi insurance can complement or replace traditional coverage, improving welfare when basis and default risks are moderate or pricing advantages are substantial. The analysis reveals how DeFi-specific frictions shape insurance demand and provides insight into how DeFi instruments may shift market structure and expand the set of attainable risk transfer outcomes.
Traditional approaches for smart contract analysis often rely on intermediate representations such as abstract syntax trees, control-flow graphs, or static single assignment form. However, these methods face limitations in capturing both semantic structures and control logic. Knowledge graphs, by contrast, offer a structured representation of entities and relations, enabling richer intermediate abstractions of contract code and supporting the use of graph query languages to identify rule-violating elements. This paper presents CKG-LLM, a framework for detecting access-control vulnerabilities in smart contracts. Leveraging the reasoning and code generation capabilities of large language models, CKG-LLM translates natural-language vulnerability patterns into executable queries over contract knowledge graphs to automatically locate vulnerable code elements. Experimental evaluation demonstrates that CKG-LLM achieves superior performance in detecting access-control vulnerabilities compared to existing tools. Finally, we discuss potential extensions of CKG-LLM as part of future research directions.
Abubakar Ibrahim Adamu, Hamidu Ardo, Najaatu Mohammed Bomai
The aim of this research is to analyze the cryptocurrency from Islamic Perspective. Cryptocurrency is a new phenomenon to Islamic Law. It is a digital currency that is neither issued by a central bank nor a public authority, but accepted as a medium of exchange by some individuals and entities and can be transferred, stored or traded electronically. Its legal nature remains unclear some are considering it as only medium of exchange while others as commodity, couple with some of its peculiar features such as anonymity of transacting parties, lack of control and supervision by a central authority, intangibility and speculation. The paper begins with brief introduction on the Islamic law principles governing commercial transactions. The paper continues with the explanation of the concept, nature and scope of cryptocurrency from Islamic Perspective. Analytical research methodology is used to analyze the work. At the end it is observed that contemporary Muslims scholars differ as to the position of cryptocurrency in Sharia. Some look at it as halal (permissible) in principle, while others look at it as haram (prohibited). However, the research recommends that a further research need to be conducted as to the actual legal status of cryptocurrency and its impact in both social and economic life of Muslims, this will assist in making a final decision on it.
We investigate the predictability of cryptocurrency returns using a comprehensive set of macroeconomic and cryptocurrency-specific factors and a set of 12 machine learning models. To enhance interpretability, we employ SHAP analysis to quantify the marginal contribution of each factor to model outputs. We further assess the economic value of predictive signals by constructing long-short and long-only portfolios. Empirically, tree-based methods, particularly random forests, deliver the highest predictive accuracy and outperform neural network and linear benchmarks, with predictability substantially stronger than that documented in equity markets. Across models, the market-to-realized-value ratio, new addresses, and active addresses consistently emerge as the most influential predictors, with higher values associated with higher expected returns. Portfolio results show that neural network-based strategies achieve the highest cumulative performance, indicating meaningful investment gains. Overall, our findings demonstrate the value of machine learning for return forecasting in the cryptocurrency market and provide practical insights for investors and financial analysts operating in highly volatile and evolving cryptocurrency environments.
YASH RAJPUT, Chaitanya Kale -, Santosh Kumar -, Asam Bhanu Prakash - · 5 authors
Know Your Customer (KYC) verification is an essential regulatory procedure in financial services to prevent fraud, money laundering and other financial crimes. Conventional approaches are centralized, redundant across institutions, and prone to data breaches. This paper presents a decentralized framework that combines blockchain smart contracts and InterPlanetary File System (IPFS) for immutably recording KYC document fingerprints while storing actual documents off-chain. We describe the system architecture, implementation choices, security and privacy considerations, and evaluation metrics. The paper includes a comparison between traditional and blockchainenabled KYC systems and discusses future directions such as Decentralized Identifiers (DIDs) and Zero-Knowledge Proofs(ZKPs).
The rapid evolution of cyber threats has exposed fundamental weaknesses in traditional intrusion detection systems, particularly those dependent on centralized architectures vulnerable to data tampering, single-point failures, and delayed threat response. As organizations face increasingly sophisticated attacks, a resilient and transparent framework for detecting and validating abnormal activity has become essential. This study examines the design and effectiveness of a blockchain-based intrusion detection system (BIDS) that leverages distributed consensus, immutable logging, and cooperative threat intelligence to enhance the reliability and responsiveness of security operations. By integrating blockchain technology with anomaly-based and signature-based identification methods, the proposed model establishes a secure environment where intrusion data cannot be altered, suppressed, or manipulated by internal or external adversaries. Through experimental evaluation across simulated network environments, the blockchain-enabled detection model demonstrates significant improvements in event accuracy, traceability, and coordination between participating nodes. The decentralized ledger structure ensures that alerts are validated collectively, reducing false positives and limiting the adversary’s ability to compromise the detection process. The integrity of recorded events also enhances forensic analysis, allowing security teams to reconstruct attack sequences with greater confidence. Additionally, the study reveals that the distributed nature of the system provides high fault tolerance, enabling continuous operation even under attempted denial-of-service conditions or node outages. Performance analysis indicates that blockchain integration does introduce additional computational overhead; however, the trade-off is compensated by the increased transparency, data authenticity, and resistance to insider threats that the system delivers. The research further highlights that smart contracts can automate rule enforcement and improve response mechanisms by triggering protective actions when predefined thresholds are met. This automation contributes to shortening detection-to-response timelines, a critical factor in mitigating fast-moving cyberattacks. Overall, the findings suggest that blockchain-powered intrusion detection represents a promising direction for strengthening network security in decentralized, cloud-based, and large-scale enterprise environments. By combining autonomous threat identification with tamper-proof logging and distributed validation, the proposed approach offers a comprehensive pathway for defending modern digital infrastructures against evolving cyber risks. The study concludes that integrating blockchain technology with intrusion detection principles not only reinforces system resilience but also lays the groundwork for more collaborative, transparent, and secure cybersecurity ecosystems.