DetectBERT: Code Vulnerability Detection

DetectBERT is a deep learning approach for identifying vulnerabilities in source code at the statement level. Utilizing transformer encoder models extracts features and learns complex relationships without predefined graph structures. DetectBERT addresses data distribution challenges using real-world code and normalizing user-defined names. Demonstrated effectiveness in Python using public datasets like CVEFixes and VUDENC, DetectBERT offers scalable, robust, and granular vulnerability detection.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/gccit63234.2024.10862235
Citations
5
Primary Topic
Software Reliability and Analysis Research
Type
article
Field-Weighted Citation Impact
2.43
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article

DetectBERT: Code Vulnerability Detection

Shantanu Sudhir Gujar
5 citations
Software Reliability and Analysis Research
2.43
article

DetectBERT: Code Vulnerability Detection

Shantanu Sudhir Gujar
article en
5 citations

Abstract

DetectBERT is a deep learning approach for identifying vulnerabilities in source code at the statement level. Utilizing transformer encoder models extracts features and learns complex relationships without predefined graph structures. DetectBERT addresses data distribution challenges using real-world code and normalizing user-defined names. Demonstrated effectiveness in Python using public datasets like CVEFixes and VUDENC, DetectBERT offers scalable, robust, and granular vulnerability detection.

Rochester Institute of Technology (US)
Openalex Percentile: Top 8%
Software Reliability and Analysis Research
2.43
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DetectBERT: Code Vulnerability Detection — Shantanu Sudhir Gujar · (2024) | TGRS Research Map | TGRS