An 'unfair queuing' mechanism that partitions CPU time between bridge-operator circuits and bridge-client circuits using a time-allocation parameter τ=0.9 reduced the circuit-clogging AUC from 0.884 to 0.520 (median-normalized) and 0.412 (mean-normalized)—indistinguishable from random guessing—in 20 PlanetLab experiments. The mechanism eliminates latency interference between the two circuit types without requiring the bridge to ever refuse connections, but introduces up to 1−τ performance loss for client traffic.

Using Tor exit nodes to query the bridge authority, the authors enumerated 247 bridge descriptors over two weeks (out of 1,716 active bridges during that period). An adversary running a relay advertising just 10 MBps of bandwidth would discover 63% of bridges that relay at least 40 circuits and 87% of bridges running at least 80 circuits, because all Tor clients proactively build circuits every 10 minutes.

§3.2 detection

A circuit-clogging attack against bridge operators—using median-normalized latency correlations—achieved an AUC of 0.884 and an equal error rate of 0.2 when distinguishing the victim bridge from innocent bridges in PlanetLab experiments with 180 victim and 180 disjoint runs. With 10 repeated clogging experiments and a majority-vote threshold, the false positive (and false negative) rate drops below 0.033, confirming a bridge operator's identity with high confidence given a candidate set of ≤4.4 bridges from the winnowing stage.

§3.4 detection

The architectural coupling of 'surfing' and 'serving' in Tor's bridge design—where enabling the bridge service is required to use Tor as a client—means a bridge always accepts connections whenever its operator is online, allowing a remote non-global adversary to probe a bridge's availability at negligible cost (less than 2 bps per bridge per status check via SYN/RST). Of the 247 enumerated bridges, only an average of 29.6 (just over 10%) were accessible at any given moment, providing a highly discriminating availability signal for intersection attacks.

§2.2, §4.2 evaluation

Cross-referencing the online/offline status of 87 monitored bridges against 186,935 Wikipedia users' edit sessions showed that 95.7% of users with 50 or more sessions matched zero bridges after winnowing. For users with 180 or more sessions (a surrogate for long-term pseudonymous activity), only 89 false positives remained among 2,329 users—a false positive rate of 0.000439—meaning that even if 10,000 Tor clients volunteer to bridge, on average only 4.4 bridges remain after the winnowing stage.

§3.3 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

The paper concludes with design guidelines for future FIA-based privacy-enhancing technologies, identifying that path-aware routing in SCION and NDN's in-network caching both create new surveillance exposure: SCION path headers reveal routing metadata to on-path censors; NDN caching at routers means content is replicated at points under censor control. The authors recommend that PETs built on FIAs treat these architectural features as threat vectors, not privacy benefits.

2025-wrana-sok-surveillance §6 dpiflow-correlation

Wrana et al. systematically assess how well existing surveillance and censorship mechanisms can target users of Future Internet Architectures (FIAs) — including NDN, SCION, XIA, and MobilityFirst — finding that DPI and flow-correlation techniques from the current internet map onto FIA traffic with moderate adaptation. The paper identifies that FIA naming/addressing schemes introduce new censorship attack surfaces (e.g., content-name-based filtering in NDN) not present in IP-based architectures.

2025-wrana-sok-surveillance §4, §5 dpiflow-correlationmeasurement-platform

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