A censor using latency analysis to classify decoy routing sessions achieves a maximum F-score that drops to nearly 0 when the base rate of decoy routing falls below 10^-4 (one in 10,000 connections). Even at higher adoption rates the F-score remains below 0.5 for most overt sites, making reliable detection infeasible without unacceptable false-positive rates on legitimate traffic.

For China (a highly connected, routing-capable adversary), the gossip protocol combined with any symmetric decoy routing design requires only 5 heavyweight downstream stations plus 880 lightweight upstream gossip stations — versus 880 heavyweight stations for purely symmetric designs. Five downstream stations alone impact 78% of routes from Chinese users, while a single downstream station already covers nearly 25% of traffic.

Table 2 / §3.2 evaluation

An asymmetric gossip protocol adds only 1.0055× bandwidth overhead for n=5 downstream stations — approximately 11 Mb/s extra on a typical 2 Gb/s OC48 link. Upstream gossip stations require no in-line blocking and impose zero additional load on overt sites, making them substantially lighter than heavyweight symmetric relay stations that must check every TLS connection for steganographic tags.

§3.3 evaluation

Between 80% and 90% of internet routes are asymmetric, with only about 10% of flows symmetric in Tier-1 (backbone) networks and roughly 70% symmetric at the network edge. This asymmetry makes decoy routing systems requiring relay stations on both upstream and downstream paths impractical for the majority of real-world deployments.

§3 evaluation

Decoy routing systems that re-encrypt TLS application data across the relay station (Slitheen, Rebound, Waterfall) are vulnerable to nonce-reuse attacks: an adversary capable of observing traffic on both sides of the relay can exploit reused GCM nonces to decrypt or modify covert traffic. Although this falls outside the standard decoy routing threat model, it poses a concrete risk to users already under heightened surveillance who face adversaries with broad network visibility.

§5.2 detection

A three-stage detection pipeline exploiting the "dual-role" behavioral fingerprint of single-IP circumvention relays achieved 23.2% recall (96/414 ground-truth relays) with a 0.18% false-positive rate against 97,651 benign TLS servers, for an overall accuracy of 99.5%. The ground-truth set covered OpenVPN, WireGuard, and SOCKS relays identified in a 17 TB single-day backbone trace (WIDE Project, April 9, 2025).

2026-almutairi-server §3.4, Table 1 traffic-shapedpiflow-correlation

Multi-censor simulations show that single-censor-optimized distribution strategies perform suboptimally in realistic multi-region deployments. When two networks have different censor strategies (e.g., one optimal, one zig-zag), the distributor cannot detect that a proxy is blocked until all censors have blocked it; this leaves clients without reachable proxies despite the proxy appearing "available" from the distributor's view. The authors conclude that "single-censor evaluation does not accurately predict more realistic deployment performance." A zig-zag censor in one region with 0.25 weight caused 44.4% collateral damage while reducing proxy lifetime to a median of 4 steps.

2026-fares-game §6, Table 4 traffic-shapeflow-correlation

The zig-zag traffic analysis attack (confirmed supported in Geedge TSG leak) rapidly enumerates all static proxy pools. With ζ_watch ∈ {4, 6} steps and a best-quality classifier (ρ_TP=0.99, ρ_FP=0.001), almost total proxy enumeration and user blockage occurs well before step 300. Even ζ_watch=2 leaves ~50% of users blocked. Collateral damage is high across all settings when ζ_watch ≥ 4: eventually ~50% of innocent servers are also blocked. However, Snowflake-style ephemeral proxies resist zig-zag effectively: reachability remains above 95% after 360 steps because churn prevents the censor from expanding its known proxy set beyond agents' direct assignments.

2026-fares-game §5.1, Fig 3, Fig 4 traffic-shapeflow-correlation

Per-flow RTTdiff detection rates are only ~20% because the majority of proxy flows connect to CDN-cached content (Cloudflare, Google, Fastly) that sits within 5ms of the proxy, suppressing the discrepancy. However, aggregating across flows per website visit yields detection rates exceeding 70%—and from the abstract, approximately 80% of top-5K domains generate at least one detectable flow—with half of those detections made within the first 60 packets. This means an adversary can reliably expose client and proxy IPs after just a few website visits.

2025-xue-discriminative §VI-C-2, Table II traffic-shapeflow-correlation

IMAP/SSL traffic on port 993 constitutes less than 1% of total ISP traffic but accounts for nearly one third of all false positives in the RTTdiff exploit, because IMAP's non-RESTful multi-connection pattern violates the request-response correlation assumption. The overall per-flow FPR is bounded at 0.6–0.7% (on par with GFW's estimated FPR against fully-encrypted proxies), but implementing a pre-filter to whitelist IMAP traffic reduces the FPR by approximately one third, making the fingerprint substantially more precise.

2025-xue-discriminative §VI-C-3, Table III traffic-shapeflow-correlation

Cross-layer RTT discrepancy (RTTdiff) is a protocol-agnostic fingerprint that exploits an inherent architectural property of all proxy setups: transport-layer sessions terminate at the proxy while application-layer sessions remain end-to-end. Evaluation across 10 proxy protocols—including VMess, Shadowsocks, VLESS, Trojan, XTLS-Vision, and obfs4-wrapped SOCKS—shows near-identical detection rates for all except obfs4, confirming the fingerprint is not tied to any specific obfuscation scheme. At FPR=0.01, per-website detection rates exceed 70% across all tested client and proxy location combinations.

2025-xue-discriminative §I, §VI-C traffic-shapeflow-correlation