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Conference proceeding
A Novel Approach to Fine-tune BERT using Non-Text Features for Enhanced Ransomware Detection
2025 3rd International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings) September 06 – 07, 2025 Michigan, USA CONFERENCE PROCEEDINGS
International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings) (Mt Pleasant, Michigan, USA , 09/06/2025–09/07/2025)
09/06/2025
Abstract
The growing complexity and volume of ransomware attacks demand advanced detection techniques that can effectively model dependencies within high-dimensional data. Traditional machine learning methods often struggle to capture nuanced relationships among features in such cybersecurity datasets. To address this problem, we propose a novel technique that transforms structured, non-linguistic data into descriptive natural language formats. This conversion facilitates the tailored refinement of a Bidirectional Encoder Representations from Transformers (BERT) architecture with optimized parameters. By leveraging BERT's multi-head self-attention mechanism, our method embeds non-textual ransomware data into semantic textual data so that multi-heads can make relationships and dependencies of tokens in different perspectives to transform instances to comprehensive latent representations where interfeature dependencies are effectively present. This allows BERT to understand contextual relevance among tokens, leading to superior classification performance. Our evaluation demonstrates that the resulting model shows dominant performance, surpassing other advanced solutions, achieving a classification accuracy of 99.21%, surpassing ensemble models (99.0%) and LSTM-based approaches (98.5%). The important finding of this novel approach is that one-third of the data points have been used to outperform other existing works. It highlights its potential and adaptability in cybersecurity domains whenever a text dataset is absent to use the natural language context for the model.
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Details
- Title
- A Novel Approach to Fine-tune BERT using Non-Text Features for Enhanced Ransomware Detection
- Publication Details
- 2025 3rd International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings) September 06 – 07, 2025 Michigan, USA CONFERENCE PROCEEDINGS
- Resource Type
- Conference proceeding
- Conference
- International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings) (Mt Pleasant, Michigan, USA , 09/06/2025–09/07/2025)
- Publisher
- IEEE
- Grant note
- National Science Foundation (10.13039/100000001)
- Copyright
- All rights reserved. Copyright ©2025 by IEEE.
- Identifiers
- 99381571824106600
- Academic Unit
- Center for Cybersecurity; Division of Academic Affairs
- Language
- English