Blockchain Security in Focus: A Comprehensive Investigation Into Threats, Smart Contract Security, Cross-Chain Bridges, and Vulnerabilities Detection Tools and Techniques

The advancement and comprehensive adoption of blockchain technology has led to momentous progression in data-critical areas such as DeFi, health sector, defense, supply chain, and beyond. Nevertheless, beside this growth, there has been a distinguished rise in both the prevalence and diversification of security vulnerabilities. Recent attacks have exploited these vulnerabilities in targeting different layers of the blockchain architecture. This paper centralizes on the security vulnerabilities, attacks, and challenges faced by blockchain systems, presenting an exhaustive taxonomical classification of blockchain layered security. It classifies diverse security issues across the different layers of blockchain architecture. With the widespread adoption of blockchain in enterprise applications, smart contracts have become a vital target for attackers, leading to significant financial and data losses. Additionally, as divergent applications are deployed across multiple blockchains, the demand for cross-chain contracts is getting progressively imperative. Investigating the security of smart contracts and cross-chain interactions is important for defending decentralized applications against vulnerabilities, assuring the secure transfer of assets among blockchains, and embracing trust and stability within the extensive blockchain ecosystem. The paper also examines different tools and techniques available in the literature for improving blockchain security, including techniques for vulnerability detection along with the surging impact of deep learning in vulnerability detection. This work presents beneficial insights into the prevailing state of blockchain security and provides a progressive prospect on the capability of intelligent, high-dimensional deep learning-based solutions to target future threats in the blockchain security space.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3556499
Citations
11
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
35.71
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article

Blockchain Security in Focus: A Comprehensive Investigation Into Threats, Smart Contract Security, Cross-Chain Bridges, and Vulnerabilities Detection Tools and Techniques

Shraddha Phansalkar, Deepa Mishra
11 citations
IEEE Access
Blockchain Technology Applications and Security
35.71
article

Blockchain Security in Focus: A Comprehensive Investigation Into Threats, Smart Contract Security, Cross-Chain Bridges, and Vulnerabilities Detection Tools and Techniques

Shraddha Phansalkar, Deepa Mishra
article en
11 citations

Abstract

The advancement and comprehensive adoption of blockchain technology has led to momentous progression in data-critical areas such as DeFi, health sector, defense, supply chain, and beyond. Nevertheless, beside this growth, there has been a distinguished rise in both the prevalence and diversification of security vulnerabilities. Recent attacks have exploited these vulnerabilities in targeting different layers of the blockchain architecture. This paper centralizes on the security vulnerabilities, attacks, and challenges faced by blockchain systems, presenting an exhaustive taxonomical classification of blockchain layered security. It classifies diverse security issues across the different layers of blockchain architecture. With the widespread adoption of blockchain in enterprise applications, smart contracts have become a vital target for attackers, leading to significant financial and data losses. Additionally, as divergent applications are deployed across multiple blockchains, the demand for cross-chain contracts is getting progressively imperative. Investigating the security of smart contracts and cross-chain interactions is important for defending decentralized applications against vulnerabilities, assuring the secure transfer of assets among blockchains, and embracing trust and stability within the extensive blockchain ecosystem. The paper also examines different tools and techniques available in the literature for improving blockchain security, including techniques for vulnerability detection along with the surging impact of deep learning in vulnerability detection. This work presents beneficial insights into the prevailing state of blockchain security and provides a progressive prospect on the capability of intelligent, high-dimensional deep learning-based solutions to target future threats in the blockchain security space.

IEEE AccessVol. 13
MIT Art, Design and Technology University (IN)
Openalex Percentile: Top 0%
Blockchain Technology Applications and Security
35.71
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