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...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohammad Jaminur Islam, Saminur Islam, Mahmud Hossain, Shahid Noor, S. M. Riazul Islam
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Future Internet
Subjects:
Online Access:https://www.mdpi.com/1999-5903/17/5/205
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850126829136904192
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
work_keys_str_mv AT mohammadjaminurislam securingblockchainsystemsalayerorientedsurveyofthreatsvulnerabilitytaxonomyanddetectionmethods
AT saminurislam securingblockchainsystemsalayerorientedsurveyofthreatsvulnerabilitytaxonomyanddetectionmethods
AT mahmudhossain securingblockchainsystemsalayerorientedsurveyofthreatsvulnerabilitytaxonomyanddetectionmethods
AT shahidnoor securingblockchainsystemsalayerorientedsurveyofthreatsvulnerabilitytaxonomyanddetectionmethods
AT smriazulislam securingblockchainsystemsalayerorientedsurveyofthreatsvulnerabilitytaxonomyanddetectionmethods