What type of study is this?

This is a Systematic Review study.

September 5, 2025Mesopotamian Journal of Big DataOpen Access

AI-Driven Smart Contract Vulnerability Detection: A Systematic Review of Methods, Challenges, and Future Prospects

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Authors

SASaad AL AzzamUCSI University RKRaenu KolandaisamyInformation Technology University GDGhassan AL Dharhani

Discussion

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Implication

This systematic review consolidates AI-driven methods and challenges in vulnerability detection within smart contracts, highlighting their effectiveness.

Key Points

AI-based methods have achieved detection accuracy above 95%, yet they require substantial computational resources.
Models like ContractWard and SCVDIE-ENSEMBLE report impressive Micro-F1 scores of 98.48% and 95.46%, respectively.
The study methodically reviewed 21 studies published from 2020 to 2024, offering a critical analysis of techniques.
Challenges persist, with AI models often dependent on labeled datasets, raising issues of generalizability to new vulnerability patterns.

Cite This Study

Azzam et al. (2025) studied this question.

synapsesocial.com/papers/68bb4d206d6d5674bcd00e32 https://doi.org/10.58496/mjbd/2025/012

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September 5, 2025Mesopotamian Journal of Big DataOpen Access

AI-Driven Smart Contract Vulnerability Detection: A Systematic Review of Methods, Challenges, and Future Prospects

View Full Paper

Ask AI

Bookmark

Authors

SASaad AL AzzamUCSI University RKRaenu KolandaisamyInformation Technology University GDGhassan AL Dharhani

Discussion

Member takes

Implication

This systematic review consolidates AI-driven methods and challenges in vulnerability detection within smart contracts, highlighting their effectiveness.

Key Points

AI-based methods have achieved detection accuracy above 95%, yet they require substantial computational resources.
Models like ContractWard and SCVDIE-ENSEMBLE report impressive Micro-F1 scores of 98.48% and 95.46%, respectively.
The study methodically reviewed 21 studies published from 2020 to 2024, offering a critical analysis of techniques.
Challenges persist, with AI models often dependent on labeled datasets, raising issues of generalizability to new vulnerability patterns.

Cite This Study

Azzam et al. (2025) studied this question.

synapsesocial.com/papers/68bb4d206d6d5674bcd00e32 https://doi.org/10.58496/mjbd/2025/012

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