FINDING · DETECTION

State-of-the-art ML-based obfs4 detection (Wang et al. decision tree) achieves 97% precision at equal base rates (λ=1) but precision collapses to 3% at a still-conservative λ=1,000; at λ=10⁶ precision approaches zero for all classifiers tested. This base-rate failure was previously uncharacterized because prior evaluations only considered balanced or near-balanced datasets.

From 2024-wails-preciselyOn Precisely Detecting Censorship Circumvention in Real-World Networks · §IV-D (Scalability), Figure 3, Table I · 2024 · Network and Distributed System Security

Implications

Tags

censors
generic
techniques
ml-classifierrandom-payload-detectdpi
defenses
obfs4

Extracted by claude-sonnet-4-6 — review before relying.