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  • 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 >

  • Open Access

    ARTICLE

    AnonymousTollPass: A Blockchain-Based Privacy-Preserving Electronic Toll Payment Model

    Jane Kim1, Soojin Lee1, Chan Yeob Yeun2, Seung-Hyun Seo1,3,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3495-3518, 2024, DOI:10.32604/cmc.2024.050461 - 20 June 2024

    Abstract As big data, Artificial Intelligence, and Vehicle-to-Everything (V2X) communication have advanced, Intelligent Transportation Systems (ITS) are being developed to enable efficient and safe transportation systems. Electronic Toll Collection (ETC), which is one of the services included in ITS systems, is an automated system that allows vehicles to pass through toll plazas without stopping for manual payment. The ETC system is widely deployed on highways due to its contribution to stabilizing the overall traffic system flow. To ensure secure and efficient toll payments, designing a distributed model for sharing toll payment information among untrusted toll service… More >

  • Open Access

    ARTICLE

    Preserving Data Secrecy and Integrity for Cloud Storage Using Smart Contracts and Cryptographic Primitives

    Maher Alharby*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2449-2463, 2024, DOI:10.32604/cmc.2024.050425 - 15 May 2024

    Abstract Cloud computing has emerged as a viable alternative to traditional computing infrastructures, offering various benefits. However, the adoption of cloud storage poses significant risks to data secrecy and integrity. This article presents an effective mechanism to preserve the secrecy and integrity of data stored on the public cloud by leveraging blockchain technology, smart contracts, and cryptographic primitives. The proposed approach utilizes a Solidity-based smart contract as an auditor for maintaining and verifying the integrity of outsourced data. To preserve data secrecy, symmetric encryption systems are employed to encrypt user data before outsourcing it. An extensive More >

  • Open Access

    ARTICLE

    Smart Contract Vulnerability Detection Method Based on Feature Graph and Multiple Attention Mechanisms

    Zhenxiang He*, Zhenyu Zhao, Ke Chen, Yanlin Liu

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3023-3045, 2024, DOI:10.32604/cmc.2024.050281 - 15 May 2024

    Abstract The fast-paced development of blockchain technology is evident. Yet, the security concerns of smart contracts represent a significant challenge to the stability and dependability of the entire blockchain ecosystem. Conventional smart contract vulnerability detection primarily relies on static analysis tools, which are less efficient and accurate. Although deep learning methods have improved detection efficiency, they are unable to fully utilize the static relationships within contracts. Therefore, we have adopted the advantages of the above two methods, combining feature extraction mode of tools with deep learning techniques. Firstly, we have constructed corresponding feature extraction mode for… More >

  • Open Access

    ARTICLE

    Blockchain-Based Key Management Scheme Using Rational Secret Sharing

    Xingfan Zhao1, Changgen Peng1,2,*, Weijie Tan2, Kun Niu1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 307-328, 2024, DOI:10.32604/cmc.2024.047975 - 25 April 2024

    Abstract Traditional blockchain key management schemes store private keys in the same location, which can easily lead to security issues such as a single point of failure. Therefore, decentralized threshold key management schemes have become a research focus for blockchain private key protection. The security of private keys for blockchain user wallet is highly related to user identity authentication and digital asset security. The threshold blockchain private key management schemes based on verifiable secret sharing have made some progress, but these schemes do not consider participants’ self-interested behavior, and require trusted nodes to keep private key… More >

  • Open Access

    REVIEW

    A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

    Huaiguang Wu, Yibo Peng, Yaqiong He*, Jinlin Fan

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 77-108, 2024, DOI:10.32604/cmes.2024.046758 - 16 April 2024

    Abstract In recent years, the number of smart contracts deployed on blockchain has exploded. However, the issue of vulnerability has caused incalculable losses. Due to the irreversible and immutability of smart contracts, vulnerability detection has become particularly important. With the popular use of neural network model, there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart contracts. This paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart contracts. Subsequently, it categorizes and presents an overview of contemporary deep learning-based tools developed… More > Graphic Abstract

    A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

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