The decentralization of Emergency Medical Services (EMS) to local administrative organizations is a critical policy initiative in Thailand aimed at enhancing service responsiveness and community participation. This study applied a prospective Health Impact Assessment (HIA) to identify positive and negative health impacts of EMS decentralization in Chonburi Province and develop evidence-based policy recommendations to guide the transition from the Ministry of Public Health to local governance. A mixed-methods approach was designed based on the six-step HIA framework. The study involved 562 participants, including EMS providers, recipients, and policymakers. Qualitative participants were selected through purposive sampling for interviews and focus groups, and quantitative participants through stratified random sampling for surveys. Qualitative data were thematically analyzed, and quantitative data were analyzed descriptively. Findings revealed both positive and negative impacts across four pre-hospital care activity domains (dispatch, incident response, referral, and administrative management) and four dimensions of well-being (physical, mental, social, and spiritual). Positive impacts included improved responsiveness, collaboration, and staff motivation, while negative impacts involved personnel shortages, communication gaps, and limited budgets. The derived policy recommendations emphasize structured workforce planning, upgraded communication systems, sustainable financing, and participatory monitoring to strengthen decentralized EMS. The use of HIA provided a systematic and participatory process that translated empirical evidence into actionable policy guidance for health service decentralization in Thailand and similar contexts.
Blockchain technology has emerged as one of the most transformative innovations of the 21st century, fundamentally reshaping how digital transactions are recorded, verified, and secured across distributed networks without centralized intermediaries. Originally conceived by Satoshi Nakamoto in 2008 as the underlying architecture for Bitcoin, blockchain has evolved far beyond cryptocurrency applications to encompass smart contracts, decentralized finance, supply chain management, healthcare systems, and enterprise solutions. This comprehensive review provides an accessible yet thorough examination of blockchain technology, targeting readers from beginner to intermediate levels seeking to understand both theoretical foundations and practical implementations. We systematically explore the foundational principles of blockchain architecture, including distributed ledger technology, block structure and chain formation, Merkle tree organization, and peer-to-peer network topologies. The paper provides in-depth analysis of cryptographic primitives including hash functions, public-key cryptography, elliptic curve digital signatures, and emerging quantum-resistant approaches. We examine diverse consensus mechanisms ranging from proof-of-work to proof-of-stake variants, Byzantine fault tolerance protocols, and hybrid approaches, analyzing their trade-offs in security, decentralization, and performance. The review extensively covers smart contract platforms with emphasis on Ethereum's architecture, vulnerability patterns, and security best practices. Critical scalability challenges are addressed through examination of layer-two solutions including Lightning Network, state channels, rollups, and sharding protocols. We analyze security threats across network, consensus, and application layers, alongside privacy-enhancing technologies such as zeroknowledge proofs and confidential transactions. Real-world applications are explored across financial services, supply chain management, healthcare, Internet of Things, and digital identity systems. The paper examines enterprise blockchain frameworks, particularly Hyperledger Fabric's permissioned architecture, comparing public and private blockchain tradeoffs. Finally, we discuss current challenges including energy consumption, regulatory uncertainty, and interoperability limitations, while exploring future research directions in quantum resistance and cross-chain protocols. By synthesizing insights from 75 peer-reviewed sources spanning foundational research, recent advances, and practical implementations, this review serves as a comprehensive resource for researchers, practitioners, and students seeking to understand blockchain technology's current state and transformative potential.
C. Selvan, M. A. Gunavathie, Sini Anna Alex, Shaik Jaffar Hussain
ABSTRACT Appropriate routing strategies are necessary for mobile ad hoc networks (MANETs) in order to facilitate effective data transfer. In order to counter the prevailing problems, the correct routing schemes will need to be selected as the default configurations are used. In this paper, a special optimal link state routing (OLSR) protocol is proposed to incorporate a deep learning methodology to facilitate efficient video streaming in MANETs. This study presents a new improved variant of the OLSR protocol, which is specially tailored to achieve efficient video streaming in MANETs. It is a radical approach that combines a deepâlearning model with blockchain technology to overcome security and reliability issues. It starts with the gathering of video content that is available publicly. In order to detect blackâhole nodes, a special twinâattentionâbased Elman spiking neural network model is applied. The reliability of the neighboring nodes is then measured by means of trust values. The pufferfish optimization algorithm, or the accuracyâaware energyâefficient multipath routing algorithm (AEMRAP), which takes into account nodeâ and linkâstability degrees, is used in making routing decisions. Interplanetary file system (IPFS) technology is used to store the data on blockchain and increase its security. The authentication of the blockchain architecture is conducted via the delegated proofâofâstake (DPoS) method that also delivers an extra protection of MANETs against unauthorized access. The study demonstrates superior performance in securing and optimizing video transmission, confirming that the extended OLSR protocol is highly effective for MANET video streaming applications. The proposed model exceeds the current approaches with a throughput of 2100 Kbps, an average end latency of 20.2 s, and a packetâdelivery ratio of 92.3%.
Alejandro Ranchal-Pedrosa, Benjamin Marsh, Lefteris Kokoris-Kogias, Alberto Sonnino
Modern blockchains increasingly adopt multi-proposer (MCP) consensus to remove single-leader bottlenecks and improve censorship resistance. However, MCP alone does not resolve how users should disseminate transactions to proposers. Today, users either naively replicate full transactions to many proposers, sacrificing goodput and exposing payloads to MEV, or target few proposers and accept weak censorship and latency guarantees. This yields a practical trilemma among censorship resistance, low latency, and reasonable cost (in fees or system goodput). We present Sedna, a user-facing protocol that replaces naive transaction replication with verifiable, rateless coding. Users privately deliver addressed symbol bundles to subsets of proposers; execution follows a deterministic order once enough symbols are finalized to decode. We prove Sedna guarantees liveness and \emph{until-decode privacy}, significantly reducing MEV exposure. Analytically, the protocol approaches the information-theoretic lower bound for bandwidth overhead, yielding a 2-3x efficiency improvement over naive replication. Sedna requires no consensus modifications, enabling incremental deployment.
We describe the Lockchain Protocol, a lightweight Bitcoin meta-protocol that enables highly efficient transaction discovery at zero marginal block space cost, and data verification without introducing any new on-chain storage mechanism. The protocol repurposes the mandatory 4-byte nLockTime field of every Bitcoin transaction as a compact metadata header. By constraining values to an unused range of past Unix timestamps greater than or equal to 500,000,000, the field can encode a protocol signal, type, variant, and sequence identifier while remaining fully valid under Bitcoin consensus and policy rules. The primary contribution of the protocol is an efficient discovery layer. Indexers can filter candidate transactions by examining a fixed-size header field, independent of transaction payload size, and only then selectively inspect heavier data such as OP RETURN outputs or witness fields. The Lockchain Protocol applies established protocol design patterns to an under-optimised problem domain, namely transaction discovery at scale, and does not claim new cryptographic primitives or storage methods.
Diodato Ferraioli, Paolo Penna, Manvir Schneider, Carmine Ventre
A central challenge in blockchain tokenomics is aligning short-term performance incentives with long-term decentralization goals. We propose a framework for algorithmic monetary policies that navigates this tradeoff in repeated participation games. Agents, characterized by type (capability) and stake, choose to participate or abstain at each round; the policy (probabilistically) selects high-type agents for task execution (maximizing throughput) while distributing rewards to sustain decentralization. We analyze equilibria under two agent behaviors: myopic (short-term utility maximization) and foresighted (multi-round planning). For myopic agents, performance-centric policies risk centralization, but foresight enables stable decentralization with some volatility to the token value. We further discuss virtual stake--a hybrid of type and stake--as an alternative approach. We show that the initial virtual stake distribution critically impacts long-term outcomes, suggesting that policies must indirectly manage decentralization.
Romance-baiting scams have become a major source of financial and emotional harm worldwide. These operations are run by organized crime syndicates that traffic thousands of people into forced labor, requiring them to build emotional intimacy with victims over weeks of text conversations before pressuring them into fraudulent cryptocurrency investments. Because the scams are inherently text-based, they raise urgent questions about the role of Large Language Models (LLMs) in both current and future automation. We investigate this intersection by interviewing 145 insiders and 5 scam victims, performing a blinded long-term conversation study comparing LLM scam agents to human operators, and executing an evaluation of commercial safety filters. Our findings show that LLMs are already widely deployed within scam organizations, with 87% of scam labor consisting of systematized conversational tasks readily susceptible to automation. In a week-long study, an LLM agent not only elicited greater trust from study participants (p=0.007) but also achieved higher compliance with requests than human operators (46% vs. 18% for humans). Meanwhile, popular safety filters detected 0.0% of romance baiting dialogues. Together, these results suggest that romance-baiting scams may be amenable to full-scale LLM automation, while existing defenses remain inadequate to prevent their expansion.
Ushbu maqolada blokcheyn texnologiyasining kelib chiqisht ishlash mexanizmi, kriptografik asoslari va real sektor uchun taqdim etayotgan ustunliklari yoritilgan shuningdek, blokcheynning tranzaksiyalarni tasdiqlash jarayoni, minerlarning vazifalari hamda xesh funksiyalari orqali ta'minlanadigan xavfsizlik mexanizmlari ko'rib chiqiladi. Maqolada pul o'tkazmalari misolida blokcheynning an'anaviy tizimlardan ustun jihatlari tahlil qilinadi va turli sohalarda qo'llanilishiga doir amalty misollar keltiriladi
In an age where the lines between finance and technology blur into an opus of digital evolution, The VDA & Crypto Convergence: Charting the Operational Pulse of the Global Crypto Exchange Ecosystem in 2025 dissects the metamorphosis of Virtual Digital Assets (VDAs) and crypto exchanges from experimental ventures to regulated pillars of modern finance. The study unveils 2025 as a watershed year- a "regulated renaissance"- where legislation such as the U.S. GENIUS Act, EU's MiCA, and Hong Kong's Stablecoin Ordinance transformed ambiguity into architecture. It examines how hybrid exchanges-the ingenious offspring of centralized speed and decentralized autonomy- symbolize the era?s financial duality, while AI-driven intelligence and tokenization redefine market participation and asset fluidity. Through the interplay of law, technology, and trust, this paper illuminates a future where the crypto economy ceases to be an outlier and becomes the central nervous system of global finance, balancing regulation and innovation like twin sails steering the same vessel through uncharted digital waters.
This comparative study investigates Chinaâs policy reform waves alongside global education trends, analyzing 334 central-level policy documents published by the National Peopleâs Congress, State Council, and Ministry of Education between 1979 and 2023. The study identifies three waves: enhancing access (1979â1990), improving quality and accountability (1991â2010), and enforcing equity (2011â2023). Even though the decentralization of finance and administration of education led, a few years later, to equity and quality concerns, several key differences to global reform trends remained: decentralization did not lead to deregulation; outcomes-based regulation complemented but did not replace input-based regulation; equity remained central, especially in the final reform wave.
BPN), MATLAB, mean absolute percentage error (MAPE) In this study, we investigate Bitcoin price volatility from December 15, 2014 to January 29, 2024 using an integrated, multisource feature set and an optimization-learning pipeline that couples Taguchi orthogonal arrays with a backpropagation network (BPN) implemented in MATLAB.Publicly available market variables were prioritized and nonquantifiable exogenous shocks were not modeled; Taguchi screening identified critical predictors and simultaneously tuned control factors (network specification, hidden-neuron count, and currency inclusion), after which the BPN was trained on aligned weekly (n = 573) and monthly (n = 108) datasets to ensure cross-market comparability.Model accuracy, assessed by mean absolute percentage error (MAPE), improved substantially after Taguchi-guided selection and configuration-weekly MAPE decreased from 3.23% to 0.36% and monthly MAPE from 6.32% to 0.07%demonstrating the efficacy of the proposed optimization framework.Out-of-sample forecasts for February-April 2025 achieved predominantly sub-10% MAPE, while high-error instances were analyzed and attributed to contributing factors, yielding decision-relevant insights for practitioners and researchers.Collectively, the results show that systematic variable selection and orthogonal-array-based model design materially enhance neural forecasts of cryptocurrency prices and provide a reproducible pathway to accurate, time-efficient prediction.
Rapid digital transformation across financial, e-commerce, and decentralized platforms has amplified the need for secure, transparent, and resilient transaction systems. Conventional security mechanisms often fail to address sophisticated cyber threats, identity fraud, and evolving attack patterns, highlighting the necessity for integrated technological solutions. The convergence of Blockchain and Artificial Intelligence (AI) establishes a robust framework that combines immutable, decentralized ledger structures with adaptive, intelligent analytics. Blockchain ensures transactional integrity, data provenance, and decentralized trust, while AI facilitates real-time anomaly detection, predictive risk scoring, and automated decision-making. This synergy enhances digital identity management, strengthens access control, and mitigates fraud by enabling continuous monitoring, behavioral analysis, and transparent verification processes. Applications extend to secure payments, smart contracts, cross-border transactions, and decentralized finance ecosystems, demonstrating improved operational efficiency, scalability, and resilience. The chapter also explores privacy-preserving computation, federated learning, and explainable AI frameworks to ensure ethical and accountable deployment of intelligent transaction systems. By integrating structural security with predictive intelligence, Blockchain-aided AI frameworks establish a next-generation foundation for secure digital transactions, fostering trust, regulatory compliance, and systemic reliability across global digital networks.
BitBallot: Final Proposal Summary Overview This document presents the final architectural design of BitBallot, an electronic voting system engineered for legally binding public elections under explicit institutional and physical deployment assumptions. Architectural Innovation BitBallot addresses long-standing limitations of end-to-end verifiable voting by separating cryptographic enforcement from institutional responsibility. * Execution Model: Rather than relying on trusted execution environments (TEEs), specialized hardware, or application logic embedded in the consensus layer, the system enforces correctness through verifiable programs (vProgs) and zero-knowledge proofs (ZKP). Infrastructure: It utilizes a public Layer-1 blockchain solely as a neutral substrate for ordering and finality. Core Contribution: Atomic Display Integrity (ADI) The central breakthrough of BitBallot is Atomic Display Integrity (ADI)âa protocol-level security property that: Cryptographically binds voter intent, interface display, and recorded ballots. Ensures a single atomic authorization event at the moment of confirmation. Maintains integrity even under re-voting semantics. Strategic Advantage: Combined with last-vote-valid voting and terminal-complete zero-knowledge tallying, BitBallot achieves strong privacy, public verifiability, and resistance to coercion without intermediate information leakage. Practical Deployment BitBallot is purpose-built for deployment on commodity hardware within supervised polling environments. Cost & Complexity: By avoiding trusted execution environments and specialized cryptographic hardware, the system significantly reduces operational complexity and deployment costs. Security: Despite using standard hardware, it preserves rigorous security guarantees through its underlying protocol design. Conclusion Together, these design choices demonstrate that large-scale, verifiable public elections can be implemented using architectures that are both cryptographically sound and institutionally realistic.
This article examines the theoretical and methodological foundations of local budget management within the public finance system, specifically addressing the complex challenges of wartime and post-war recovery. The research systematizes diverse scientific approaches to positioning local budgets, proposing a refined definition of the local budget as a multi-functional financial instrument essential for regional strategic development and the provision of public services. The study argues that the multifaceted role of the local budget is a prerequisite for ensuring the socio-economic security and stability of territorial communities amidst current military and economic pressures. The authors establish that efficient public finance management is fundamental to national economic growth and financial system stability. A primary contribution of the research is the development of a conceptual model for local budget management, structured as an integrated complex with clearly defined objectives, subjects, and functional principles. This model incorporates regulatory, legal, and informational support mechanisms, allowing for the effective allocation of funds and increased transparency in the context of decentralization. The study emphasizes that both internal and external factors determine the effectiveness of decision-making and the choice of regional management strategies. Ultimately, the proposed model enhances the accountability of local authorities and reduces uncertainty in financial activities. By providing a framework for robust budgetary analysis, this conceptual approach fosters sustainable development and strengthens the financial capacity of Ukrainian regions. The findings provide a theoretical basis for improving the budgetary security of territorial communities during both conflict and reconstruction phases.
Abstract This paper revisits Virgo, a well-known transparent zero-knowledge proof system that has been used in many subsequent studies. Through our analysis, we uncover previously overlooked limitations and several exploitable security vulnerabilities within Virgoâs zkVPD protocol design and implementation. We subsequently address these issues and improve Virgoâs zkVPD protocol. Our improvements feature simplified but more efficient VPD and zkVPD algorithms, offering enhanced support for computations over binary fields and their extension fields.
Recently, it has been noted that the convergence of blockchain technology presents a promising paradigm for secure, privacy-preserving, and transparent healthcare systems. Moreover, Digital Twins enable real-time replication of patients, hospital operations, and medical devices, and their dependence on continuous sensitive data streams introduces the latest trust and Cybersecurity challenges. A systematic literature review aims to investigate how distributed ledger and blockchain technologies have been applied to secure healthcare digital twins from 2020 to 2025. Furthermore, the review addresses the proposed architecture of blockchain, the security objectives targeted, integration approaches within digital twins, and evaluation methods with limitations. The study follows PRISMA 2020 guidelines. Web of Sciences, IEEE Xplore, PubMed, Scopus, and ACM Digital Library were searched from January 2020 to October 2025 by using defined Boolean queries. Also, the focus of the inclusion criteria is on peer-reviewed studies that discussed blockchain for DT security in healthcare. Data extraction captured blockchain type, metadata, security mechanisms, DT domain, and evaluation methods. From the 487 identified records, only 20 successfully met the inclusion criteria. The fact behind it is that most studies only employed permissioned blockchains like Quorum and Hyperledger integrated with digital twins for monitoring patients, device lifecycle tracking, and data provenance. Some main security objectives include provenance assurance, access control, and integrity. Moreover, only some studies provide formal threat analysis or real-world deployment. Blockchain technology is reliable because it increases digital twin security through immutability, smart-contract-based governance, and decentralized trust. However, interoperability, scalability, and privacy-preserving computation remain the main barriers for clinical adoption.
This paper applies wavelet quantile correlation to research on the relationship among renewable energy stocks, investor sentiment, and the cryptocurrency market. The empirical results indicated that under extremely negative conditions, in both the short and medium run, renewable energy stocks and cryptocurrencies are negatively correlated, implying that during such periods, renewable energy stocks can be used as a safe haven for cryptocurrencies. The opposite happens when the market is average or booming. This indicates that investors tend to invest simultaneously in these two promising asset classes when the market performs well. Under varied market conditions, FGI correlates positively with cryptocurrency, demonstrating sentiment influences price patterns. Moreover, the correlation between FGI and renewable energy stocks further validates the relationship between cryptocurrencies and renewable energy stocks. These findings can be used to improve the prediction of market trends by investors using sentiment indices and to devise more effective portfolio diversification strategies that minimize risk amid an evolving market.
Mbonigaba Celestin*, J. Azhar Mohamed**, G. R. Gnana Raja** & K. Vinayakan**
This analysis uses data from the IMF, OECD, and the World Bank, studies the viability of decentralized finance within nine economies. The multilevel structural equation model attributes 84 percent of the variance of legitimacy to blockchain reporting (ÎČ=0.41), AI analytics (ÎČ=0.29), audit accessibility (ÎČ=0.22), and the intensity of oversight (ÎČ=0.12). The study claims unalterable data combined with algorithmic assurance as novel pillars of accountability and trust. Policy implications advocate for the adoption of cohesive, auditable trust frameworks alongside AI-powered auditing solutions to streamline transparency and fortified cross-border accountability in decentralized finance.
Financial institutions are currently faced with suffering never experienced before as they strive to guarantee the privacy of data and address the demands of regulation to report and cooperate in machine learning. This paper proposes PrivChain-AI, a novel blockchain-based federated learning system designed to facilitate secure and privacy-preserving financial reporting and access control. The proposed framework will integrate three key components: differential privacy, homomorphic encryption, and smart contract-based governance, enabling cooperative model training across financial institutions while preventing the leakage of sensitive information. PrivChain-AI is a hierarchical design that incorporates permissioned consensus protocols and utilises zero-knowledge proof verification to authenticate transactions. It has been demonstrated that the performance is higher than that of the actual financial data, with an outcome of 94.7% accuracy in fraud recognition at the cost of e-differentiation privacy, where Ï” = 1.0. It is 40% faster in terms of communication overhead and ensures regulatory compliance, as it features immutable audit trails. The analysis of performances reveals that a privacy preservation metric improves by 78%, and access control granularity is improved by 62% compared to the current state-of-the-art approaches. The PrivChain-AI paradigm introduced provides a new analytical model for safe, collaborative finance, meeting the highest standards and ensuring compliance with relevant regulatory jurisdictions.
The rapid growth of IoT devices in smart home environments has introduced significant challenges in ensuring secure, scalable, and efficient communication among heterogeneous devices. Centralized architectures suffer from a single point of failure, while blockchain-only solutions face high latency, limiting their use in real-time control. To address these issues, we propose a multi-layered decentralized framework that combines a consortium blockchain, a trusted off-chain coordinator, group-based zero-knowledge proofs (ZKPs), and a two-tiered access control policy (ACP) architecture. The consortium blockchain provides an immutable ledger for device identities and foundational, coarse-grained ACP enforcement through smart contracts, ensuring tamper-proof trust. For privacy-preserving mutual authentication, a group-based ZKP protocol enables collective device authorization without revealing sensitive keys. The off-chain coordinator complements this by enforcing dynamic security mechanisms, including fine-grained ACPv2 checksâsuch as rate limits, time-of-day restrictions, and device telemetryâin addition to anomaly detection for behavioral risk assessment. This proposed hybrid structure achieves both immutability and high efficiency over traditional methods. A performance evaluation highlighted the frameworkâs efficiency by demonstrating that the core ZKP verification for a 500-device group can be completed in just 190 ms. The framework drastically reduces on-chain costs, with critical access control policy transactions consuming only 82,748 gasâa reduction of over 90% compared to benchmarked on-chain systems. The complete end-to-end workflow, from user request to secure session establishment, has a latency bound of approximately 3s. Formal security verification with the BAN and AVISPA tools validates resilience against common attacks, including man-in-the-middle, replay, and impersonation, while static analysis using the Slither framework confirms the absence of critical vulnerabilities in the smart contract code. By combining an immutable on-chain foundation with intelligent, dynamic off-chain enforcement, our proposed framework provides a uniquely resilient, scalable, and adaptive security solution for modern smart home systems.
Michele Fabi, Viraj Nadkarni, Leonardo Leone, Matheus V. X. Ferreira
<div> We develop an axiomatic theory for Automated Market Makers (AMMs) in local energy sharing markets and analyze the Markov Perfect Equilibrium of the resulting economy with a Mean-Field Game. In this game, heterogeneous prosumers solve a Bellman equation to optimize energy consumption, storage, and exchanges. Our axioms identify a class of mechanisms with linear, Lipschitz continuous payment functions, where prices decrease with the aggregate supply-to-demand ratio of energy. We prove that implementing batch execution and concentrated liquidity allows standard design conditions from decentralized finance-quasi-concavity, monotonicity, and homotheticity-to construct AMMs that satisfy our axioms. The resulting AMMs are budget-balanced and achieve ex-ante efficiency, contrasting with the strategy-proof, expost optimal VCG mechanism. Since the AMM implements a Potential Game, we solve its equilibrium by first computing the social planner's optimum and then decentralizing the allocation. Numerical experiments using data from the Paris administrative region suggest that the prosumer community can achieve gains from trade up to 40% relative to the grid-only benchmark. </div>
In decentralized finance (DeFi), designing fixed-income lending automated market makers (AMMs) is extremely challenging due to time-related complexities. Moreover, existing protocols only support single-maturity lending. Building upon the BondMM protocol, this paper argues that its mathematical invariants are sufficiently elegant to be generalized to arbitrary maturities. This paper thus propose an improved design, BondMM-A, which supports lending activities of any maturity. By integrating fixed-income instruments of varying maturities into a single smart contract, BondMM-A offers users and liquidity providers (LPs) greater operational freedom and capital efficiency. Experimental results show that BondMM-A performs excellently in terms of interest rate stability and financial robustness.
Damilare E. Bakare, Adekemi Olawunmi Amoo, Mary T. Onifade
The health insurance sector has been facing many challenges recently, such as fraudulent activities in insurance claims, data breaches, and high transaction costs, particularly with existing systems built on the Ethereum network, which negatively affect its efficiency and effectiveness.These challenges undermine the trust and financials of insurance providers while compromising the privacy of the patient's health records.To address this issue, this study proposes a conceptual framework that uses zero-knowledge proof within the blockchain system and is deployed on the Polygon Network for its low transaction fees and higher throughput.The proposed model allows the verification of an insurance claim without revealing sensitive patient health records, ensuring privacy while preventing fraudulent activities.In this conceptual design, the hospital can issue verifiable proof of treatment, appointment, and bill that shows the validity of the insurance claim without revealing the underlying health record to the insurer.This study, therefore, contributes to supporting research in decentralized applications for healthcare insurance by presenting a conceptual model and comprehensively analyzing the feasibility, rather than a full-scale implementation.It also emphasizes the need to preserve privacy in sensitive domains and the potential benefits of blockchain and ZKP integration.In conclusion, the research's findings show that, in theory, integrating ZKP with blockchain technology can enhance healthcare insurance processes in terms of reliability, efficiency, privacy, and security.However, further research and practical development are required to realize and evaluate a fully operational system.