Improving DNS Exfiltration Detection via Transformer Pretraining
We study whether in-domain pretraining of Bidirectional Encoder Representations from Transformer (BERT) model improves subdomain-level detection of exfiltration at low false positive rates. While previous work mostly examines fine-tuned generic Transformers, it does not aim to isolate the effect of pretraining on the downstream task of classification. To address this gap, we develop a controlled pipeline where we freeze operating points on validation and transfer them to the test set, thus enabling clean ablations across different label and pretraining budgets. Our results show significant improvements in the left tail of the Receiver Operating Characteristic (ROC) curve, especially again...
| Authors | Miloš Tomić, Aleksa Cvetanović, Predrag Tadić |
|---|---|
| Primary category | cs.CR |
| Published | 9 April 2026 |
| Last updated at source | 9 April 2026 |
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