Encore's architecture turns ordinary web visitors into measurement vantage points, which the researchers argue prevents censors from detecting and disabling dedicated measurement probes. However, this benefit comes with the trade-off that the individuals whose browsers are co-opted face potential legal or physical risk that differs by country and by the specific censored content accessed.

The Encore system collected censorship measurements from 88,260 distinct IP addresses across 170 countries over seven months via installations by at least 17 volunteer website operators. China, India, the United Kingdom, and Brazil each contributed at least 1,000 measurements; Egypt, South Korea, Iran, Pakistan, Turkey, and Saudi Arabia each contributed more than 100.

Introduction evaluation

The paper identifies a structural conflict between Internet research's scalability imperative — where a project processing millions of devices is considered superior — and human-subjects ethics frameworks designed to minimize the number of people exposed to risk. Under U.S. law, Encore is compliant because it exploits known, intentional web functionality (the same-origin policy's cross-origin request mechanism) and provides an opt-out mechanism, but the authors note this compliance does not transfer to all jurisdictions where measurements occur.

Legal Compliance / Discussion policy

ACM SIGCOMM 2015's program committee accepted the Encore paper with an unprecedented 'signing statement' after heated ethical debate. The committee's core objections were: (1) users accessing censored URLs might face repercussions in regimes without due process; (2) most users under censorship would be unlikely to consent to the measurements; and (3) unlike ad-tracker third-party requests, Encore requests do not reflect any user intent.

Ethical Oversight by Program Committees policy

To mitigate harm, Encore restricted its URL list to Twitter, Facebook, and YouTube on the grounds that widgets from these domains appear in ordinary web browsing, making Encore-induced cross-origin requests statistically indistinguishable from normal traffic. The authors argued that this renders the risk comparable to baseline browsing, though the SIGCOMM committee disputed whether contextual equivalence with ad-tracking constitutes adequate ethical justification.

Mitigating Harm policy

Combining all three active probing attacks in an Internet-wide scan of 30 million HTTPS servers identified approximately 15,000 hosts (0.05%) behaving like ShadowTLS relays; of these only 6,000 presented TLS certificates for Alexa Top 1000 domains. The scan successfully discovered all four researcher-operated ShadowTLS relays planted as ground truth.

2023-wang-chasing §3.2, Table 2 active-probingmeasurement-platform

The authors' ISP Tap dataset yielded 129,000 unique response sets across 433,286 endpoints while ZMap's 1.5 million endpoints produced only 31,000 unique sets — with over 42% of ZMap endpoints behaving identically (infinite timeout, no data) due to firewall chaff. This vantage-point bias means the effective false-positive rate a censor faces when targeting ISP-observed traffic is ~28× lower than against random scans (0.02% vs 0.56% for MTProto), making ISP-scale active probing far more actionable than Internet-wide scanning alone.

2020-frolov-detecting §III-B, §V-D, Fig. 2 active-probingmeasurement-platform

High-speed Internet-wide scanning enables a censor or attacker to locate every publicly reachable host vulnerable to a newly disclosed flaw within hours of disclosure; in a concrete example, 3.4 million UPnP-vulnerable devices were identified in under 2 hours — faster than network operators could apply patches — with a 150-SLOC probe module written in approximately 4 hours.

2013-durumeric-zmap §4.3 active-probingmeasurement-platform

By scanning ports 443 and 9001 and fingerprinting responses with Tor's TLS v1 cipher-suite handshake pattern, ZMap identified 79–86% of all allocated Tor bridge fingerprints in a single scan, demonstrating that bridges whose protocol is distinguishable are largely discoverable through comprehensive Internet-wide scanning even though their addresses are not publicly listed.

2013-durumeric-zmap §4.4 active-probingtls-fingerprintmeasurement-platform

The largest single source of censored domains in the GNL is MESA lab's SNI monitoring dataset (E21-SNI-Top200w.txt) containing 57,362 censored domains, and E21-SNI-Top120W-20221020.txt with 36,467 domains—totaling over 93K domains from network tap data alone for a single country (E21 = Ethiopia per InterSecLab attribution). A separate Xinjiang dataset (XJ-CUCC-SNI-Top200w.txt) contains 13,604 domains. These datasets "do not seem to come from popular domain lists, and instead appear to be gathered from network taps," confirming that Geedge builds censorship target lists directly from passive traffic observation.

2026-sheffey-geedge §4.2, Table 3 dpisni-blockingmeasurement-platform

Of 6,915,266 domains extracted from the 572 GiB Geedge Networks Leak (GNL), 298,955 censored domains (93.7% of all GNL-censored domains) appear in neither Tranco top-1M nor CitizenLab test lists. Measurements across China (Guangzhou/Nanjing), Myanmar, Pakistan, and Algeria confirmed censorship via DNS injection and SNI-based TLS connection termination. The GNL covers 25–62% of Tranco-censored domains across countries, showing substantial but incomplete overlap. This vendor-side ground truth reveals a censorship surface roughly two orders of magnitude larger than curated academic test lists.

2026-sheffey-geedge §4.1, Table 2 dpisni-blockingdns-poisoningmeasurement-platform