Securing Blockchain Systems: A Layer-Oriented Survey of Threats, Vulnerability Taxonomy, and Detection Methods
Blockchain technology is emerging as a pivotal framework to enhance the security of internet-based systems, especially as advancements in machine learning (ML), artificial intelligence (AI), and cyber–physical systems such as smart grids and IoT applications in healthcare continue to accelerate. Alt...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Future Internet |
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| Online Access: | https://www.mdpi.com/1999-5903/17/5/205 |
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| _version_ | 1850126829136904192 |
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| author | Mohammad Jaminur Islam Saminur Islam Mahmud Hossain Shahid Noor S. M. Riazul Islam |
| author_facet | Mohammad Jaminur Islam Saminur Islam Mahmud Hossain Shahid Noor S. M. Riazul Islam |
| author_sort | Mohammad Jaminur Islam |
| collection | DOAJ |
| description | Blockchain technology is emerging as a pivotal framework to enhance the security of internet-based systems, especially as advancements in machine learning (ML), artificial intelligence (AI), and cyber–physical systems such as smart grids and IoT applications in healthcare continue to accelerate. Although these innovations promise significant improvements, security remains a critical challenge. Blockchain offers a secure foundation for integrating diverse technologies; however, vulnerabilities—including adversarial exploits—can undermine performance and compromise application reliability. To address these risks effectively, it is essential to comprehensively analyze the vulnerability landscape of blockchain systems. This paper contributes in two key ways. First, it presents a unique layer-based framework for analyzing and illustrating security attacks within blockchain architectures. Second, it introduces a novel taxonomy that classifies existing research on blockchain vulnerability detection. Our analysis reveals that while ML and deep learning offer promising approaches for detecting vulnerabilities, their effectiveness often depends on access to extensive and high-quality datasets. Additionally, the layer-based framework demonstrates that vulnerabilities span all layers of a blockchain system, with attacks frequently targeting the consensus process, network integrity, and smart contract code. Overall, this paper provides a comprehensive overview of blockchain security threats and detection methods, emphasizing the need for a multifaceted approach to safeguard these evolving systems. |
| format | Article |
| id | doaj-art-08b05b8e8b244d93afd0ae6aaa068355 |
| institution | OA Journals |
| issn | 1999-5903 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj-art-08b05b8e8b244d93afd0ae6aaa0683552025-08-20T02:33:50ZengMDPI AGFuture Internet1999-59032025-05-0117520510.3390/fi17050205Securing Blockchain Systems: A Layer-Oriented Survey of Threats, Vulnerability Taxonomy, and Detection MethodsMohammad Jaminur Islam0Saminur Islam1Mahmud Hossain2Shahid Noor3S. M. Riazul Islam4Department of Computer Science, University of California, Riverside, CA 92521, USADepartment of Computer Science, North Carolina State University, Raleigh, NC 27695, USADepartment of Private Certificate Authority, Amazon Web Services (AWS), Herndon, VA 20171, USADepartment of Computer Science, Northern Kentucky University, Highland Heights, KY 41099, USASchool of Natural and Computing Sciences, University of Aberdeen, Aberdeen AB24 3FX, UKBlockchain technology is emerging as a pivotal framework to enhance the security of internet-based systems, especially as advancements in machine learning (ML), artificial intelligence (AI), and cyber–physical systems such as smart grids and IoT applications in healthcare continue to accelerate. Although these innovations promise significant improvements, security remains a critical challenge. Blockchain offers a secure foundation for integrating diverse technologies; however, vulnerabilities—including adversarial exploits—can undermine performance and compromise application reliability. To address these risks effectively, it is essential to comprehensively analyze the vulnerability landscape of blockchain systems. This paper contributes in two key ways. First, it presents a unique layer-based framework for analyzing and illustrating security attacks within blockchain architectures. Second, it introduces a novel taxonomy that classifies existing research on blockchain vulnerability detection. Our analysis reveals that while ML and deep learning offer promising approaches for detecting vulnerabilities, their effectiveness often depends on access to extensive and high-quality datasets. Additionally, the layer-based framework demonstrates that vulnerabilities span all layers of a blockchain system, with attacks frequently targeting the consensus process, network integrity, and smart contract code. Overall, this paper provides a comprehensive overview of blockchain security threats and detection methods, emphasizing the need for a multifaceted approach to safeguard these evolving systems.https://www.mdpi.com/1999-5903/17/5/205blockchain securityvulnerability detectionmachine learningdeep learningconsensus attackssmart contract security |
| spellingShingle | Mohammad Jaminur Islam Saminur Islam Mahmud Hossain Shahid Noor S. M. Riazul Islam Securing Blockchain Systems: A Layer-Oriented Survey of Threats, Vulnerability Taxonomy, and Detection Methods Future Internet blockchain security vulnerability detection machine learning deep learning consensus attacks smart contract security |
| title | Securing Blockchain Systems: A Layer-Oriented Survey of Threats, Vulnerability Taxonomy, and Detection Methods |
| title_full | Securing Blockchain Systems: A Layer-Oriented Survey of Threats, Vulnerability Taxonomy, and Detection Methods |
| title_fullStr | Securing Blockchain Systems: A Layer-Oriented Survey of Threats, Vulnerability Taxonomy, and Detection Methods |
| title_full_unstemmed | Securing Blockchain Systems: A Layer-Oriented Survey of Threats, Vulnerability Taxonomy, and Detection Methods |
| title_short | Securing Blockchain Systems: A Layer-Oriented Survey of Threats, Vulnerability Taxonomy, and Detection Methods |
| title_sort | securing blockchain systems a layer oriented survey of threats vulnerability taxonomy and detection methods |
| topic | blockchain security vulnerability detection machine learning deep learning consensus attacks smart contract security |
| url | https://www.mdpi.com/1999-5903/17/5/205 |
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