The Energy Internet has become a hot topic for the integration of sustainable energies. However, as a result, there are numerous sustainable energy forms and participants, the system is extremely complex, and some key issues are difficult to overcome, such as the control and management of distributed sustainable energy forms. On the other hand, blockchain technology consists of distributed data storage, peer-to-peer transmission, a consensus mechanism, encryption algorithms, and smart contracts. Applying the technical advantages of the blockchain to the Energy Internet can solve many of the problems that hinder its development. The purpose of this paper is to review the development of blockchain and the Energy Internet, and provide some references for the possible applications of blockchain technology to the Energy Internet. Firstly, the definition and characteristics of blockchain and the Energy Internet are introduced in detail. Secondly, the compatibility of the two is analyzed. Then, several application scenarios of blockchain in the Energy Internet are put forward. Finally, the challenges that still exist when applying the current blockchain technology to the Energy Internet are analyzed.
The ability of blockchain technology to record transactions on distributed ledgers offers new opportunities for governments to improve transparency, prevent fraud, and establish trust in the public sector. However, blockchain adoption and use in the context of e-Government is rather unexplored in academic literature. In this paper, we systematically review relevant research to understand the current research topics, challenges and future directions regarding blockchain adoption for e-Government. The results show that the adoption of blockchain-based applications in e-Government is still very limited and there is a lack of empirical evidence. The main challenges faced in blockchain adoption are predominantly presented as technological aspects such as security, scalability and flexibility. From an organizational point of view, the issues of acceptability and the need of new governance models are presented as the main barriers to adoption. Moreover, the lack of legal and regulatory support is identified as the main environmental barrier of adoption. Based on the challenges presented in the literature, we propose future research questions that need to be addressed to inform how the public sector should approach the blockchain technology adoption.
As a trust machine, blockchain was recently introduced to the public to provide an immutable, consensus based and transparent system in the Fintech field. However, there are ongoing efforts to apply blockchain to other fields where trust and value are essential. In this paper, we suggest Gcoin blockchain as the base of the data flow of drugs to create transparent drug transaction data. Additionally, the regulation model of the drug supply chain could be altered from the inspection and examination only model to the surveillance net model, and every unit that is involved in the drug supply chain would be able to participate simultaneously to prevent counterfeit drugs and to protect public health, including patients.
IntroductionThe insurance industry has evolved into a global multi-billion-dollar sector, with health insurance gaining prominence due to escalating healthcare costs. This rapid expansion brings heightened risks, including data breaches, fraud, and difficulties in safeguarding sensitive policyholder information. Indonesia’s National Health Insurance (NHI)—one of the largest national insurance programs worldwide—covers over 200 million citizens, aiming to provide universal healthcare. However, this extensive coverage raises substantial concerns about data privacy and traceability, particularly during the claim process, as policyholders currently have limited control over and insight into how their data is accessed and used.MethodsTo address these challenges, we propose a blockchain-based model designed to enhance policyholders’ private control over data access and improve traceability throughout the NHI claim process. Our approach employs three complementary architectures—functional, logical, and physical—to guide system implementation. The functional architecture is illustrated via a use case diagram that outlines the roles and actions of each participant. The logical architecture employs Business Process Model and Notation (BPMN) diagrams to depict the revised process flow and data movement, while also incorporating a layered design concept. The physical data architecture provides a class diagram detailing data structures and actor relationships. A proof-of-concept prototype was developed to demonstrate the core functionalities of the new system.ResultsBy integrating blockchain technology, our prototype ensures authorized access, bolsters data privacy, and maintains data integrity in the NHI claim workflow. The system’s layered design and use of smart contracts guarantee transparent, tamper-proof record-keeping, while parallelized processes in the logical architecture streamline claims handling. Initial tests of the prototype confirm the feasibility and robustness of the proposed solution, illustrating how blockchain can facilitate traceability and preserve confidentiality.DiscussionThe blockchain-based design addresses pressing concerns surrounding data security and accountability in large-scale health insurance systems. It allows policyholders to monitor and control their personal information, reducing the likelihood of unauthorized use. Furthermore, the transparent and immutable ledger enables stakeholders to verify data provenance and transactions, enhancing trust. Future work will focus on scalability, regulatory compliance, and integration with existing healthcare IT infrastructures to fully realize the benefits of blockchain in national health insurance programs.
Telemedicine diagnosis has become a more flexible and convenient way to receive diagnoses, which is of great significance in enhancing diagnosis, cutting costs, and serving remote users. However, telemedicine faces many security problems, such as the complexity of user authentication, the balance of the existing biometric factor authentication scheme, the unpredictability of user behavior, and the difficulty of unified authentication due to the differences in the security standards and authentication mechanisms of different trust domains, which affect the sustainable development of telemedicine. To address the above issues, this paper presents an identity management scheme based on multi-factor authentication and dynamic trust evaluation for telemedicine. Its authentication combines iris recognition for secure biometric verification, smart cards for encrypted credential storage, and static passwords for supplementary verification, addressing scenarios like facial coverage in medical settings. The scheme dynamically adjusts authentication based on attack rates, login anomalies, and service durations. By integrating ShangMi cryptographic algorithms and blockchain, it optimizes performance, achieving 35% lower communication overhead than previous protocols. A security analysis shows it resists impersonation, man-in-the-middle, and password modification attacks while preserving user anonymity. System evaluation meets authoritative standards, validating its practicality. This scheme balances security and efficiency, providing a strong basis for telemedicine’s long-term viability.
With the development of artificial intelligence and blockchain technology, the training of deep learning models needs large computing resources. Meanwhile, the Proof of Work (PoW) consensus mechanism in blockchain systems often leads to the wastage of computing resources. This article combines distributed deep learning (DDL) with blockchain technology and proposes a blockchain consensus scheme based on the proof of distributed deep learning work (BCDDL) to reduce the waste of computing resources in blockchain. BCDDL treats DDL training as a mining task and allocates different training data to different nodes based on their computing power to improve the utilization rate of computing resources. In order to balance the demand and supply of computing resources and incentivize nodes to participate in training tasks and consensus, a dynamic incentive mechanism based on task size and computing resources (DIM-TSCR) is proposed. In addition, in order to reduce the impact of malicious nodes on the accuracy of the global model, a model aggregation algorithm based on training data size and model accuracy (MAA-TM) is designed. Experiments demonstrate that BCDDL can significantly increase the utilization rate of computing resources and diminish the impact of malicious nodes on the accuracy of the global model.
Amid growing global urgency for climate action, innovative financial mechanisms are critical for advancing renewable energy transitions in developing economies. This study investigates the role of financial technology (fintech), with a focus on foreign portfolio investment (FPI), in influencing renewable energy investment (REINV) across 54 developing countries in Africa, Asia, and Latin America from 2010 to 2023. Employing a multi-method empirical approach, comprising Spatial Durbin Models (SDM), Quantile Regression (QR), Stochastic Frontier Analysis (SFA), and Spatial Quantile Regression (SQR), the research captures spatial dependencies, distributional heterogeneity, and efficiency dynamics. The SDM results indicate that FPI significantly increases REINV both directly (1.112) and indirectly through spillover effects (0.445), supported by significant spatial autocorrelation (0.334). Economic development and institutional quality also play key roles, with GDP per capita and institutional quality exerting positive and significant direct effects. Quantile regression reveals that FPI has a stronger influence at higher quantiles of REINV, with coefficients rising from 0.745 to 1.445, highlighting distributional inequality in fintech impact. SFA results show that FPI also enhances technical efficiency (0.912), though diminishing marginal returns are evident. Greater financial depth and electricity access reduce inefficiency, while inflation worsens it. Spatial quantile regression further confirms that regional spillovers are more pronounced among high-investment countries, underscoring the role of spatial dynamics in clean energy financing. The findings suggest that fintech can be a catalyst for renewable energy growth, especially in countries with higher institutional and financial capacity. Policy recommendations include strengthening digital infrastructure, enhancing regulatory coordination, and ensuring macroeconomic stability to fully leverage fintech's potential. Future research should explore emerging fintech tools such as decentralized finance and blockchain-based green bonds.
Decentralized Finance (DeFi) has revolutionized the financial landscape, with protocols like Uniswap offering innovative automated market-making mechanisms. This article explores the development of a backtesting framework specifically tailored for Concentrated Liquidity Market Makers (CLMMs). The focus is on leveraging the liquidity distribution approximated using a parametric model to estimate the rewards within liquidity pools. The article details the design, implementation, and insights derived from this novel approach to backtesting within the context of Uniswap V3. The developed backtester was successfully utilized to assess reward levels across several pools using historical data from 2023 (pools Uniswap V3 for pairs of altcoins, stablecoins, and USDC/ETH with different fee levels). Moreover, the error in modeling the level of rewards for the period under review for each pool was less than 1%. This demonstrated the effectiveness of the backtester in quantifying liquidity pool rewards and its potential in estimating revenues of Liquidity Provider (LP) as part of the pool rewards, which is the focus of our next research. The backtester serves as a tool to simulate trading strategies and liquidity provision scenarios, providing a quantitative assessment of potential returns for LPs. By incorporating statistical tools to mirror CLMM pool liquidity dynamics, this framework can be further leveraged for strategy enhancement and risk evaluation for LPs operating within decentralized exchanges.
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 checks—such as rate limits, time-of-day restrictions, and device telemetry—in 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 framework’s 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 gas—a 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.
Annika Aebli, Fabienne Silberstein-Bamford, Joshua S. Bamford
Cryptocurrency technologies have spawned a vast network of millions of users. One notable aspect of crypto spaces is the emergence of vibrant communities that form around specific projects, with supporters gathering on interactive online platforms and demonstrating a strong sense of collective identity. Despite its pseudonymous and “trustless” nature, crypto has become an instrument for establishing social ties that seem remarkably robust. However, the factors that influence establishing social bonds in highly dispersed, pseudonymous crypto spaces with minimal in-person interaction have remained largely unexplored so far. Using a mixed-method approach, this study examines the factors that shape community formation in the crypto space. In an initial step, based on 26 semi-structured, qualitative interviews, we explore factors that may influence group formation in crypto spaces. In a second step, we develop a quantitative questionnaire using items generated from these interviews to measure the effect of the identified factors on group formation, using a sample of 111 crypto users. Group formation is operationalised as an identity fusion scale, reflecting the tendency for individuals to merge their sense of self with that of a social group to which they belong. The results show that social reward, a promising outlook, and participant’s investment level predict identity fusion with crypto communities. This study contributes to the understanding of social bonding processes in pseudonymous crypto spaces.