SoK: Where Do Flow Labels Come From? Auditing Label Provenance in Encrypted Traffic Benchmarks

• URL: http://arxiv.org/abs/2609.02140v1
• Date: Wed, 02 Sep 2026 05:51:42 GMT
• Title: SoK: Where Do Flow Labels Come From? Auditing Label Provenance in Encrypted Traffic Benchmarks
• Abstract summary: Encrypted traffic classification infers semantics beyond the flow record from transport-layer observables.<n>Recent systematizations scrutinize model in- puts and data splits; we systematize the complementary label side.<n>Across 14 benchmark entries, we identify two recurring label-side strategies.
• Score: 5.044786941116112
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Encrypted traffic classification infers semantics beyond the flow record from transport-layer observables, and supervised training rests on labels that hold for the individual flow they are attached to. Recent systematizations scrutinize model in- puts and data splits; we systematize the complementary label side. Across 14 audited benchmark entries, we identify two recurring label-side strategies: coarse inheritance, which risks labelling flows the evidence does not cover, and overstrict filtering, which keeps only self-attesting flows and risks dis- carding relevant ones. No audited entry exposes a countable pre-selection population, and the task objects downstream papers attach to the same labels disagree with the recovered record in 8 of 23 referenced cells. Under strict side-channel features we derive a representation-relative ceiling on bal- anced accuracy for any classifier restricted to those features: on the public benchmarks that inherit, it ranges from 0.56 to 0.76. On the filtering side, only 24.95% of connections in our fully captured corpus carry an observable SNI of their own; yet the discarded connections raise macro accuracy from 0.44 to 0.65 through same-run co-occurrence features. We end with recommendations for benchmark builders and users.

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