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InfoResearchPeer-reviewed
LitCVit: A Lightweight Self-Supervised Contrastive Vision Transformer for Encrypted Malicious Traffic Detection
- Published
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Summary
LitCVit is a lightweight self-supervised contrastive Vision Transformer for detecting malicious encrypted traffic without decryption or manually engineered features. The authors report 98.10% average detection accuracy and a 98.08% F1-score on benchmark datasets, with a 2.49% F1 gain over the best prior model and an 8.7x reduction in inference time versus the best existing self-supervised approach.