Cryptocurrency is a novel exploration of a form of currency that proposes a decentralized electronic payment scheme based on blockchain technology and cryptographic theory. While cryptocurrency has the security characteristics of being distributed and tamper-proof, increasing market demand has led to a rise in malicious transactions and attacks, thereby exposing cryptocurrency to vulnerabilities, privacy issues, and security threats. Particularly concerning are the emerging types of attacks and threats, which have made securing cryptocurrency increasingly urgent. Therefore, this paper classifies existing cryptocurrency security threats and attacks into five fundamental categories based on the blockchain infrastructure and analyzes in detail the vulnerability principles exploited by each type of threat and attack. Additionally, the paper examines the attackers' logic and methods and successfully reproduces the vulnerabilities. Furthermore, the author summarizes the existing detection and defense solutions and evaluates them, all of which provide important references for ensuring the security of cryptocurrency. Finally, the paper discusses the future development trends of cryptocurrency, as well as the public challenges it may face.
Dynamic spectrum sharing (DSS) is essential for 6G networks, yet existing blockchain-based DSS solutions often lack an integrated approach that simultaneously addresses trust, allocation fairness, and system scalability. This paper proposes HierSpectrumChain, a hierarchical blockchain framework that incorporates a global main chain, localized sub-chains, and a smart-contract based Stackelberg auction for credible and automated spectrum allocation. The system model formalizes interactions among spectrum holders, secondary users, and sub-chain validators, enabling transparent bidding and decentralized coordination. A proof-of-concept implementation on an Ethereum Ganache environment evaluates the functional correctness of the auction workflow and measures throughput under varying client loads. While the evaluation is limited to a single-node testbed, the results demonstrate the feasibility of the proposed architecture and establish a basis for future multi-peer experiments on permissioned blockchains. This work provides a coherent design and initial validation for blockchain-enabled DSS in 6G networks.
The widespread adoption of emerging technologies in healthcare has led to an exponential increase in medical data generation. However, the security of healthcare data has not kept pace, with frequent breaches and unauthorized access posing substantial threats to patient privacy and the integrity of healthcare systems. Although existing access control frameworks offer partial solutions for secure data access, they fall short in authorization granularity, privacy preservation, and large-scale, high-frequency access. To bridge these critical gaps, we propose a novel role-based access control (RBAC) framework that enables secure and efficient management of large-scale, high-frequency data access. The framework first introduces a real-time access behavior analysis algorithm. It then integrates Ethereum smart contract technology with the RBAC model to construct high-performance, scalable access control contracts. Subsequently, the framework simulates the EMR interaction process in a representative healthcare scenario. Through rigorous security evaluations and experimental simulations, we demonstrate that the proposed framework enables robust accessor management, secure data sharing, and effective support for large-scale, high-frequency access while maintaining operational efficiency. This work offers a scalable and practical solution to healthcare data security in the era of big data and population aging.
Blockchain technology benefits companies in handling various use cases, including real estate, voting, fitness tracking, intellectual rights, the Internet of Things (IoTs), and vaccine distribution. Several technologies proposed in the literature seek to support businesses, enterprises, and state institutions in improving their operations and services, primarily in the financial sector. Although the existing technologies provide the needed service, the “trust” issue remains challenging. This differs from salary management in some state institutions in developing countries, such as Ghana. This paper presents a novel approach by implementing a permissioned blockchain-based system using Hyperledger Fabric integrated with RSA encryption to address the transparency, trust, and fraud challenges in salary-grade structure management. Unlike existing blockchain payroll applications, this work explicitly targets the salary grade adjustment processes within state institutions, providing a real-world prototype validated with actual agency data. In this paper, we implemented the blockchain technology for salary management. We use the Hyperledger Fabric platform to build a trusted platform to aid State Institution X (siX) in sharing data, validating transactions, securing data, and auditing transactions among its stakeholders— a prototype design aimed at reducing the wage bill and ensuring transparency in the public service payroll. The results showed that blockchain operations increased transparency in the payroll system among stakeholders by 100%. The application developed was secure and could track all the changes made by the relevant stakeholders in salary management.
Web3 is the next-generation internet, utilizing blockchain technology to power decentralized applications and give users greater control. However, the scalability limitations of blockchain create performance bottlenecks that hinder Web3’s overall processing capabilities. Among current scalability solutions, multi-chain architecture has been considered a promising approach with high flexibility. However, current multi-chain architecture lacks portability to existing blockchains and relies on relayers to solve timing issues in the interoperability process. The lack of portability makes it challenging for existing blockchains to adopt the current multi-chain architecture, significantly impeding multi-chain promotion. Moreover, relying on relayers to address timing issues leads to low efficiency and potential reliability risks. This paper introduces Zunesha, a multi-chain architecture that designs a smart-contractbased multi-chain toolkit (STACK) to provide a portable multi-chain architecture. Additionally, it introduces the Dynasty-Based Consensus Node Set Verification (DB-CNSV) protocol as a foundational safety mechanism to eliminate relayers in the interoperability process and address timing issues. Our evaluation shows that Zunesha significantly enhances the overall performance of the blockchain. As the number of subchains increases, the throughput grows almost linearly. Furthermore, the performance of inter-chain transactions surpasses that of the current mainstream multi-chain architecture, Cosmos.
In the rapidly evolving decentralized finance (DeFi) ecosystem, ensuring efficient and interoperable transaction mechanisms is a critical challenge. This paper introduces a strategic optimization model for a blockchain-based token exchange platform, leveraging Coincidence of Wants (CoWs), multi-chain Automated Market Makers (AMMs), and an on-chain solver auction mechanism to enhance transaction efficiency and cross-chain interoperability in DeFi. In our model, users specify their transaction intents, while solvers, selected through a competitive auction based on game theory principles, compete to find the most efficient execution pathways, considering liquidity availability and market constraints. This approach not only facilitates seamless cross-chain transaction flows, but also optimizes the efficiency of existing solvers and reduces the reliance on centralized mechanisms. Our model’s effectiveness is validated through extensive simulation experiments, where performance with various order inputs and AMM constraints demonstrates a transaction completion rate increase ranging from 26.1% to 46.1% compared to the CoWs-only model, thereby enhancing user welfare and market fairness. The proposed model offers broad applicability for efficient, interoperable cross-chain transactions, positioning it to make a significant impact on the DeFi landscape.
consensus protocols and peer-provided proofs are the necessary components used to establish trust in blockchain systems. Verifiable proofs that guarantee an elapsed time based on security components have emerged as alternatives to energy-intensive Proof of Work (PoW). These proofs are well-suited for embedding consensus protocols running on resource-constrained devices. This paper proposes Trust@TEE.TIME, an experimental platform designed to instrument and characterize several proof mechanisms within embedded devices. Our platform is proof-agnostic, allowing it to accommodate various proof generation mechanisms without modifications to the underlying hardware or architecture. It comprises Systems on Module featuring an ARM Cortex-A7 processor with a Trusted Execution Environment (TEE) and a Trusted Platform Module (TPM). These components are collaboratively used to ensure secure proof generation. This paper is an extension of a previous paper which introduced Proof of Hardware Time (PoHT). It provides a more detailed description of the experimental platform and a comparison of power consumption and time delay with different average elapsed time between blocks. In addition, we show that PoHT achieves an average power reduction factor of 7 to 117 compared to PoW.
This work presents SOvNet, a blockchain-agnostic hybrid solution that combines the privacy of proprietary systems with the resilience of public blockchains. SOvNet is a private network that publishes cryptographic fingerprints of its data on public blockchains, while aiming to simplify the management of personal data and transactions. The network is maintained by a group of nodes that updates the system status and provides cryptographic proofs of data processing to the network users. Designed for governments and enterprises, SOvNet supports services such as document management, real-world asset digitalisation, and digital payments. It also supports communication between SOvNet instances with minimal user-side overhead. The user interface to interact with SOvNet implements only lightweight operations, allowing for deployment on personal devices, including laptops and smartphones.
This paper investigates the information sharing strategies of green supply chains, greenwashing, and blockchain technology. The unobservable green activities in the manufacturing process references to those aspects of logistics activities that are imperceptible to consumers. To ensure that consumers perceive authentic green information without being influenced by greenwashing, the retailer and manufacturer can collaborate on establishing a blockchain platform for sharing the manufacturer’s carbon footprint data. The research findings indicate that the manufacturer may be motivated to share its carbon footprint information to stimulate consumer demand for green products. Additionally, the retailer may proactively invest in constructing a blockchain platform to facilitate the sharing of the manufacturer’s carbon footprint data and enhance sales profitability. Analysis indicates that when consumers possess a higher anticipated level of unobservable greenness and exhibit greater sensitivity to green issues, there is an enhanced motivation for both manufacturers and retailers to implement blockchain technology. Interestingly, due to the construction costs associated with implementing the blockchain platform, the manufacturer and retailer are more likely to collaborate on this endeavor. However, this shift in the information sharing structure benefits all members of the supply chain, resulting in a mutually beneficial outcome. Furthermore, the dominant blockchain strategy is influenced by factors such as cost and market strategy.
Sharding is a key technology to improve the scalability of blockchain, and cross-shard transaction protocols are the core of sharding to ensure transaction atomicity and consistency. Many scholars have conducted related research, including two-phase commit (2PC), transaction splitting, relay transactions, and deterministic ordering. However, there remains a challenge in balancing the efficiency and atomicity of cross-shard transactions (CTXs). Thus, this paper proposes a parallel and atomicity-guaranteed cross-shard transaction protocol, BMDS-Shard. Firstly, by decoupling cross-shard transactions into synchronized transactions in the source and target shards through beacon nodes, and automatically identifying cross-shard processing flows, we assign higher processing priority within shards, thereby solving the inefficiency of relay transactions. Secondly, based on a multi-beacon node data snapshot mechanism, we ensure instant and reliable state data feedback to the source shard, addressing the insufficient atomicity of transaction splitting. Finally, we have implemented the BMDS-Shard protocol, conducted theoretical analysis, and performed experimental validation on the BlockEmulator platform. Both theoretical and experimental results demonstrate that while guaranteeing transaction atomicity, our protocol reduces cross-shard transaction confirmation latency by 65.82% and 65.06% compared to existing relay transaction protocols Monoxide and BrokerChain, respectively.
With the development of artificial intelligence and big data, data has become an important part of production factors, and the sharing and transaction of data have a very high importance. Through the storage service of the cloud data transaction platform, users can send data to the cloud platform remotely, and flexibly access and transmit data through the Internet anytime and anywhere. However, this approach faces growing data security concerns. When users transmit data to the cloud, they will not have full control over their data. Data stored in the cloud may be altered, deleted, leaked, or misappropriated, especially in public cloud environments. Many current data transaction platforms simply adopt a decentralized model to avoid this problem, but still perform poorly in the face of massive transaction scenarios. In addition, when the data demander receives the required data, there is the problem of denying the transaction, which challenges the availability of the data transaction platform and affects the trust of the data transaction participants in the transaction platform. This paper proposes a secure searchable-encryption-based data transaction protocol (SDTP) utilizing blockchain technology and searchable encryption. In the proposed protocol, the transaction platform does not gain access to the provider’s raw data, and the data provider has all decisionmaking rights over the data. The data demander can search for the target encrypted data using only keywords before receiving the original data authorized by the data provider. In addition, blockchain technology, with its decentralized and tamper-proof characteristics, has made important contributions to the transformation of traditional centralized data transaction platforms, and the entire data transaction process is recorded on the blockchain, effectively preventing problems such as demander denial and data tampering. In this paper, a formal verification tool is used to ensure that the proposed protocol meets the ideal security standard expected by the secure data transaction protocol, and the security of the protocol against attacks is proved from the perspective of non-formal theoretical analysis.
The rapid growth of decentralized finance (DeFi) has provided numerous benefits, but it has also presented significant economic security challenges. One of the most critical issues is Maximum Extractable Value (MEV). MEV refers to the opportunities for miners or validators to earn additional profits by altering the order of transactions. However, current MEV detection methods have notable limitations. These include poor adaptability of algorithms, the vastness of the search space, and the inefficiency of methods that rely on traditional heuristic approaches. To overcome these challenges, we introduces a reinforcement learning-based MEV optimization system for blockchain—RL-BES (Reinforcement Learning for Blockchain Economic Security). This system employs two deep reinforcement learning networks to optimize transaction ordering and template parameters, integrated with Monte Carlo Tree Search (MCTS) for effective path exploration. Furthermore, we presents a custom model evaluation tool designed to adjust various networks and parameters, facilitating the analysis of the best algorithmic solutions for on-chain MEV extraction. Experimental results indicate that the RL-BES system excels in multiple DeFi applications. It demonstrates faster convergence and consistently surpasses the performance of Flashbot and other similar detection tools.
random beacons are crucial components in blockchain consensus, secure multiparty computation, and decentralized applications, providing high-quality randomness for these applications. However, random beacon services operated by a single organization face centralization issues and cannot be fully trusted by mission-critical applications due to possible breaches and collusion. Asynchronous distributed random beacon protocols are proposed as a promising alternative to such centralized services, since they can generate high-quality randomnesses that are unbiased and unpredictable for critical applications in the adversarial asynchronous Internet. However, they either suffer from expensive communication overhead or lack accommodation for efficient dynamic participation. To address these issues, we propose a practical asynchronous random beacon protocol that can be efficiently reconfigured to support rotations of participating nodes, reducing the reconfiguration’s communication complexity from O(λn3) to O(λ κn2), where λ is the cryptography security parameter, n is the size of nodes in the network, and κ is the small size of a any-trust sub-committee (which approximates a constant number about several dozens). We also demonstrate the performance and security of our scheme through thorough analysis and extensive experiments.
Blockchain technology establishes trust among participants through technical means. However, some malicious nodes may compromise this trust through short-range reorganization attacks for their interest. This paper develops an agent-based model to systematically analyze Proof-of-Stake short-range reorganization attacks, where three types of agents interact through distributed consensus mechanisms with ex-ante, fine-grained, and ex-post reorganization attack strategies. Through rigorous simulation of agent decision-making dynamics, we identify that: (1) Compared with ex-ante reorganization, the ratio of malicious nodes required for ex-post reorganization is much larger. (2) Increasing the node number increases the difficulty of ex-ante and ex-post reorganization. (3) The number of nodes affects ex-post reorganization attacks more significantly than ex-ante attacks. (4) Fine-grained reorganization significantly reduces attack difficulty
Consensus mechanisms are fundamental to maintaining consistency in distributed systems. With the advent of Web 3.0, blockchain has revealed limitations of traditional Delegated Proof of Stake (DPoS) consensus mechanisms. To address these issues, we propose a novel Quadratic Voting-based DPoS (Q-DPoS) consensus mechanism. Our approach integrates Quadratic Voting into DPoS to optimize voting power distribution, vote counting, and reward settlement processes, thereby incentivizing participation from users with lower stakes while reducing the concentration of influence. To prevent the system from reverting to a linear reward structure under Sybil Attacks, we introduce admission rules and vote similarity detection mechanisms to strengthen its robustness. Simulation results demonstrate that Q-DPoS significantly increases voter participation and alleviates stake centralization, thereby enhancing overall decentralization. Additionally, theoretical analysis grounded in game theory confirms that the proposed mechanism effectively diversifies voting preferences, contributing to a more balanced and resilient consensus mechanism suitable for Web 3.0 ecosystem.
Airdrops represent a pivotal strategic instrument for Web3 projects, serving to distribute free tokens and motivate early adoption. However, the popularity of these tokens has fueled the emergence of airdrop hunters—individuals who exploit multiple transactions to acquire disproportionate amounts of tokens unfairly. This phenomenon threatens the integrity and fairness of the Web3 community. Current detection methods struggle with high false-positive rates, harming legitimate users, and require significant computational resources for training. Furthermore, these methods face challenges in adapting to the evolving tactics of airdrop hunters, leading to diminished detection accuracy and efficiency. We introduce ARTEMIX, a community-boosting-based framework that integrates custom-engineered features and community detection techniques to identify airdrop hunters in NFT transactions. Using data from the Blur NFT market, ARTEMIX demonstrates superior accuracy and efficiency, outperforming existing graph-based inference models, achieving an F1 score of 0.898. This approach provides a scalable and effective solution to anomaly detection in the Web3 ecosystem, promoting a more secure and equitable environment for token distributions.
Blockchain-enabled subcontracting model has been developed to address the issue of bid shopping in construction projects. However, the impact of this blockchain application on the decision-making of project stakeholders and its economic outcomes has not been thoroughly examined. This study establishes a game-theoretic framework to evaluate the economic implications of stakeholders' behaviors in the construction project subcontracting process. Utilizing this framework, the study investigates how the blockchain-enabled subcontracting model influences stakeholders’ decision-making and economic outcomes when compared to the traditional subcontracting model. The findings of this examination indicate that the blockchain application can effectively reduce opportunistic behaviors, leading to mutually beneficial outcomes for the stakeholders. This outcome contributes to the existing knowledge by 1) elucidating the practical implications of blockchain-based subcontracting models in the construction industry, bridging the gap between new technological applications and industry practices, and 2) illustrating that blockchain technology promotes ethical decision-making among General Contractors (GC) and Subcontractors (Subs) during the subcontracting process, ultimately improving quality and profitability by reducing the risks of claims and disputes.
With the strong support of various countries' policies, blockchain technology is booming in all walks of life, and the demand for blockchain evaluation is also growing. Relevant authoritative organizations have begun to formulate blockchain evaluation standards and carry out evaluations on the blockchain platforms and application products, providing reliable information for the government, industry authorities, blockchain users and investors in the blockchain selection stage. This article introduces mainstream blockchain evaluation institutions, analyzes the status of blockchain evaluation standards, sorts out blockchain evaluation tools and methods, and summarizes the current development of the blockchain evaluation industry based on the relevant status quo. This article also gives some suggestions for future development in terms of improving the implementation of blockchain evaluation standards, improving blockchain evaluation tools, formulating international standards for blockchain evaluation, and strengthening the training of blockchain evaluation talents.
