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  • Open Access

    ARTICLE

    Ponzi Scheme Detection for Smart Contracts Based on Oversampling

    Yafei Liu1,2, Yuling Chen1,2,*, Xuewei Wang3, Yuxiang Yang2, Chaoyue Tan2

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.069152 - 10 November 2025

    Abstract As blockchain technology rapidly evolves, smart contracts have seen widespread adoption in financial transactions and beyond. However, the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems. Although numerous detection techniques have been proposed, existing methods suffer from significant limitations, such as class imbalance and insufficient modeling of transaction-related semantic features. To address these challenges, this paper proposes an oversampling-based detection framework for Ponzi smart contracts. We enhance the Adaptive Synthetic Sampling (ADASYN) algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions. This enhancement facilitates the… More >

  • Open Access

    REVIEW

    Computer Modeling Approaches for Blockchain-Driven Supply Chain Intelligence: A Review on Enhancing Transparency, Security, and Efficiency

    Puranam Revanth Kumar1, Gouse Baig Mohammad2, Pallati Narsimhulu3, Dharnisha Narasappa4, Lakshmana Phaneendra Maguluri5, Subhav Singh6,7,8, Shitharth Selvarajan9,10,11,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2779-2818, 2025, DOI:10.32604/cmes.2025.066365 - 30 September 2025

    Abstract Blockchain Technology (BT) has emerged as a transformative solution for improving the efficacy, security, and transparency of supply chain intelligence. Traditional Supply Chain Management (SCM) systems frequently have problems such as data silos, a lack of visibility in real time, fraudulent activities, and inefficiencies in tracking and traceability. Blockchain’s decentralized and irreversible ledger offers a solid foundation for dealing with these issues; it facilitates trust, security, and the sharing of data in real-time among all parties involved. Through an examination of critical technologies, methodology, and applications, this paper delves deeply into computer modeling based-blockchain framework… More >

  • Open Access

    ARTICLE

    Blockchain and Smart Contracts: An Effective Approach for the Transaction Security & Privacy in Electronic Medical Records

    Amal Al-Rasheed1, Hashim Ali2,*, Rahim Khan2,*, Aamir Saeed3

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3419-3436, 2025, DOI:10.32604/cmc.2025.065156 - 23 September 2025

    Abstract In the domain of Electronic Medical Records (EMRs), emerging technologies are crucial to addressing longstanding concerns surrounding transaction security and patient privacy. This paper explores the integration of smart contracts and blockchain technology as a robust framework for securing sensitive healthcare data. By leveraging the decentralized and immutable nature of blockchain, the proposed approach ensures transparency, integrity, and traceability of EMR transactions, effectively mitigating risks of unauthorized access and data tampering. Smart contracts further enhance this framework by enabling the automation and enforcement of secure transactions, eliminating reliance on intermediaries and reducing the potential for… More >

  • Open Access

    ARTICLE

    A Hybrid Machine Learning and Blockchain Framework for IoT DDoS Mitigation

    Singamaneni Krishnapriya1,2,*, Sukhvinder Singh1

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1849-1881, 2025, DOI:10.32604/cmes.2025.068326 - 31 August 2025

    Abstract The explosive expansion of the Internet of Things (IoT) systems has increased the imperative to have strong and robust solutions to cyber Security, especially to curtail Distributed Denial of Service (DDoS) attacks, which can cripple critical infrastructure. The proposed framework presented in the current paper is a new hybrid scheme that induces deep learning-based traffic classification and blockchain-enabled mitigation to make intelligent, decentralized, and real-time DDoS countermeasures in an IoT network. The proposed model fuses the extracted deep features with statistical features and trains them by using traditional machine-learning algorithms, which makes them more accurate… More > Graphic Abstract

    A Hybrid Machine Learning and Blockchain Framework for IoT DDoS Mitigation

  • Open Access

    ARTICLE

    Smart Contract-Aided Attribute-Based Signature Algorithm with Non-Monotonic Access Structures

    Xin Xu1,*, Zhen Yang2, Yongfeng Huang1

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5019-5035, 2025, DOI:10.32604/cmc.2025.061046 - 19 May 2025

    Abstract Attribute-Based Signature (ABS) is a powerful cryptographic primitive that enables fine-grained access control in distributed systems. However, its high computational cost makes it unsuitable for resource-constrained environments, and traditional monotonic access structures are inadequate for handling increasingly complex access policies. In this paper, we propose a novel smart contract-assisted ABS (SC-ABS) algorithm that supports non-monotonic access structures, aiming to reduce client computing overhead while providing more expressive and flexible access control. The SC-ABS scheme extends the monotonic access structure by introducing the concept of negative attributes, allowing for more complex and dynamic access policies. By… More >

  • Open Access

    ARTICLE

    GMS: A Novel Method for Detecting Reentrancy Vulnerabilities in Smart Contracts

    Dawei Xu1,2, Fan Huang1, Jiaxin Zhang1, Yunfang Liang1, Baokun Zheng3,*, Jian Zhao1

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2207-2220, 2025, DOI:10.32604/cmc.2025.061455 - 16 April 2025

    Abstract With the rapid proliferation of Internet of Things (IoT) devices, ensuring their communication security has become increasingly important. Blockchain and smart contract technologies, with their decentralized nature, provide strong security guarantees for IoT. However, at the same time, smart contracts themselves face numerous security challenges, among which reentrancy vulnerabilities are particularly prominent. Existing detection tools for reentrancy vulnerabilities often suffer from high false positive and false negative rates due to their reliance on identifying patterns related to specific transfer functions. To address these limitations, this paper proposes a novel detection method that combines pattern matching… More >

  • Open Access

    ARTICLE

    Smart Contract Vulnerability Detection Using Large Language Models and Graph Structural Analysis

    Ra-Yeon Choi1, Yeji Song2, Minsoo Jang1, Taekyung Kim3, Jinhyun Ahn4,*, Dong-Hyuk Im5,*

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 785-801, 2025, DOI:10.32604/cmc.2025.061185 - 26 March 2025

    Abstract Smart contracts are self-executing programs on blockchains that manage complex business logic with transparency and integrity. However, their immutability after deployment makes programming errors particularly critical, as such errors can be exploited to compromise blockchain security. Existing vulnerability detection methods often rely on fixed rules or target specific vulnerabilities, limiting their scalability and adaptability to diverse smart contract scenarios. Furthermore, natural language processing approaches for source code analysis frequently fail to capture program flow, which is essential for identifying structural vulnerabilities. To address these limitations, we propose a novel model that integrates textual and structural… More >

  • Open Access

    ARTICLE

    Detecting Ethereum Ponzi Scheme Based on Hybrid Sampling for Smart Contract

    Yuanjun Qu, Xiameng Si*, Haiyan Kang, Hanlin Zhou

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3111-3130, 2025, DOI:10.32604/cmc.2024.057368 - 17 February 2025

    Abstract With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, its anonymity has provided new ways for Ponzi schemes to commit fraud, posing significant risks to investors. Current research still has some limitations, for example, Ponzi schemes are difficult to detect in the early stages of smart contract deployment, and data imbalance is not considered. In addition, there is room for improving the detection accuracy. To address the above issues, this paper proposes LT-SPSD… More >

  • Open Access

    ARTICLE

    FADSF: A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

    Yan Sun, Caiyun Liu, Jun Li, Yitong Liu*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2351-2362, 2024, DOI:10.32604/cmc.2024.048903 - 15 August 2024

    Abstract With the development of technology, the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage terminal. The data of ICV (intelligent connected vehicles) is the key to organically maximizing their efficiency. However, in the context of increasingly strict global data security supervision and compliance, numerous problems, including complex types of connected vehicle data, poor data collaboration between the IT (information technology) domain and OT (operation technology) domain, different data format standards, lack of shared trust sources, difficulty in ensuring the quality of shared data, lack of data… More >

  • Open Access

    REVIEW

    A Systematic Review and Performance Evaluation of Open-Source Tools for Smart Contract Vulnerability Detection

    Yaqiong He, Jinlin Fan*, Huaiguang Wu

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 995-1032, 2024, DOI:10.32604/cmc.2024.052887 - 18 July 2024

    Abstract With the rise of blockchain technology, the security issues of smart contracts have become increasingly critical. Despite the availability of numerous smart contract vulnerability detection tools, many face challenges such as slow updates, usability issues, and limited installation methods. These challenges hinder the adoption and practicality of these tools. This paper examines smart contract vulnerability detection tools from 2016 to 2023, sourced from the Web of Science (WOS) and Google Scholar. By systematically collecting, screening, and synthesizing relevant research, 38 open-source tools that provide installation methods were selected for further investigation. From a developer’s perspective,… More >

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