mlsanityData to 14 Oct 2026

Security Vulnerability Detection Using Deep Learning Natural Language Processing

arXiv 2105.02388 ↗First posted 6 May 2021cs.CR cs.AIcited by 12

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Abstract (arXiv)

Detecting security vulnerabilities in software before they are exploited has been a challenging problem for decades. Traditional code analysis methods have been proposed, but are often ineffective and inefficient. In this work, we model software vulnerability detection as a natural language processing (NLP) problem with source code treated as texts, and address the automated software venerability detection with recent advanced deep learning NLP models assisted by transfer learning on written English. For training and testing, we have preprocessed the NIST NVD/SARD databases and built a dataset of over 100,000 files in C programming language with 123 types of vulnerabilities. The extensive experiments generate the best performance of over 93% accuracy in detecting security vulnerabilities.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 16 of its 25 references that are in the map. First posted on arXiv 6 May 2021.

Builds on

16 of 25 references.

References · 16

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4 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 5; 2024: 3; 2025: 1; 2026: 1.

12 papers.

  1. 2022Transformer-Based Language Models for Software Vulnerability Detectioncited by 39
  2. 2023SecureFalcon: Are We There Yet in Automated Software Vulnerability Detection with LLMs?cited by 13
  3. 2023HW-V2W-Map: Hardware Vulnerability to Weakness Mapping Framework for Root Cause Analysis with GPT-assisted Mitigation Suggestioncited by 8
  4. 2024A Survey of Source Code Representations for Machine Learning-Based Cybersecurity Taskscited by 5
  5. 2025VISION: Robust and Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentationcited by 3
  6. 2024Comparing Unidirectional, Bidirectional, and Word2vec Models for Discovering Vulnerabilities in Compiled Lifted Codecited by 1
  7. 2026SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repaircited by 1
  8. 2022FastPacket: Towards Pre-trained Packets Embedding based on FastText for next-generation NIDScited by 0
  9. 2023Software Vulnerability Prediction Knowledge Transferring Between Programming Languagescited by 0
  10. 2023An experimental study in Real-time Facial Emotion Recognition on new 3RL datasetcited by 0
  11. 2023Vulnerability Detection Using Two-Stage Deep Learning Modelscited by 0
  12. 2024Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Pointscited by 0