The authors propose two countermeasures: (1) widespread adoption of traffic splitting so not all user traffic is routed through a single VPN tunnel, neutralizing the single-destination session signature; and (2) VPN servers should rotate at random intervals so that no prolonged session to one IP accumulates enough packets to trigger the threshold T.

IoT devices pose the primary false-positive risk: many IoT devices (printers, smart bulbs, cameras, vacuum cleaners) maintain very few sessions with a small number of fixed cloud IPs — behaviorally similar to a VPN client. In the CIC IoT 2022 dataset, only 2 devices were misclassified (a Google Nest Cam connecting to nexusapi-us1.dropcam.com and a device using Alibaba cloud) out of the full dataset with WINDOW=300 s and T=500 packets.

§IV-B, §IV-C detection

The threat model requires no DPI and was fully implemented as a Linux kernel module on a NETGEAR R6120 with only a 580 MHz processor, 16 MB ROM, and 64 MB RAM, adding negligible overhead. Unlike ML-based or DPI-based VPN classifiers, the statistical model operates pre-NAT on per-device private IP flows, making it immune to obfuscation techniques that alter packet payloads or disguise protocol handshakes.

§I, §IV detection

A passive, router-level VPN fingerprinting technique exploits the design convention that all user traffic is tunneled to a single VPN server IP. By counting packets per device-to-IP session at the home router and flagging sessions where PACKETS_COUNT exceeds threshold T=500 within WINDOW=300 seconds, the method achieved a 100% detection rate for all VPN implementations that route all traffic through one server, with zero false positives across uncontrolled 4-day experiments.

§III–IV detection

Testing 9 popular VPN providers (ProtonVPN, Hide.me, Turbo VPN, Kaspersky VPN, Hotspot Shield, Secure VPN, Fast VPN Pro, VPN Super, VPN Gate), 7 were successfully detected. KasperskyVPN evaded detection because it exchanged keepalive packets with a secondary server exactly every 300 seconds, matching the chosen WINDOW, causing the session counter to reset. Hotspot Shield evaded because of previously documented traffic leakage where not all traffic is tunneled.

§IV-D, Table II evaluation

MCCI (AS197207) blocks proxy IPs proportionally to observed connection volume: the more connections a phantom IP receives, the faster it gets blocked. A controlled experiment with a fresh /27 IPv4 subnet divided into 7 /30 sub-ranges with increasing weights confirmed that higher-weighted subnets were blocked first, demonstrating that the censor infers proxy IP reputation from traffic rate rather than from a static blocklist.

2025-alaraj-iran-refraction §4.2.3 ip-blockingtraffic-shape

The report documents IMSI-catcher and mobile-network interception deployments in Pakistan that complement fixed-line DPI infrastructure. Mobile broadband users (dominant internet access mode in Pakistan) face surveillance at both the carrier level and via OTT platform coercion, with major platforms (YouTube, Twitter/X, TikTok) receiving and complying with blocking and content takedown orders from PTA, reducing the scope of accessible content even for users not running circumvention tools.

2025-amnesty-pakistan-shadows §6 traffic-shapeip-blocking

Amnesty International's 102-page investigation identifies a multi-vendor surveillance stack deployed in Pakistan: Chinese DPI (Geedge/MESA-derived), Canadian social-media monitoring (Netsweeper), and Emirati commercial spyware (Pegasus and FinFisher). The system enables deep packet inspection, SNI-based filtering, and traffic-shape classification at national scale, including targeted interception of encrypted messaging apps and VPN traffic.

2025-amnesty-pakistan-shadows §3, §5 dpisni-blockingip-blockingtraffic-shapeml-classifier

InterSecLab's 76-page analysis of the Geedge/MESA leak (based on nine months of indexing and translating >100,000 documents) characterizes the Tiangou Secure Gateway (TSG) product line as a commercially deployable detection stack that combines deep packet inspection, real-time mobile subscriber monitoring, active probing, ML-based traffic classifiers, and granular per-region rule sets. TSG is not a research prototype — leaked documentation includes deployment timelines and client government interactions for Kazakhstan, Ethiopia, Pakistan, Myanmar, and one unnamed country, with censorship rules explicitly tailored to each region.

2025-interseclab-internet-coup §3–§5 (InterSecLab report) dpiactive-probingml-classifiersni-blockingip-blockingtraffic-shapefully-encrypted-detect

Justice for Myanmar documents that Geedge Networks supplied Myanmar's military junta with GFW-derived surveillance and censorship infrastructure under Belt and Road frameworks following the February 2021 coup. The deployed system (Tiangou Secure Gateway / TSG) incorporates the same DPI, active-probing, and ML-classifier capabilities as the domestic Chinese GFW, giving Myanmar one of the most technically capable censorship systems in Southeast Asia.

2025-jfm-silk-road-surveillance §3, §5 dpisni-blockingip-blockingtraffic-shapeml-classifieractive-probing

The report documents that Myanmar's military has used its TSG-based infrastructure to execute targeted throttling and selective shutdowns of specific services and platforms, not only blanket internet shutdowns. This includes selective disruption of VPNs and circumvention tools during periods of civil unrest, demonstrating that Myanmar's censors have operationalized the granular per-service traffic control capabilities documented in the Geedge/MESA leak.

2025-jfm-silk-road-surveillance §5 throttlingip-blockingtraffic-shape