Prolonged conflicts with gradual infrastructure recovery represent a third category of detection gap: IODA-style automated systems struggle to distinguish ongoing partial outages from normal network fluctuation, causing recovery-phase disruptions in conflict zones (e.g., Myanmar, Sudan) to go undocumented in automated records.

Comparative analysis of 73 unmatched events (2022 onward) between IODA's automated network-level detection and Access Now's #KeepItOn Shutdown Tracker reveals systematic documentation gaps — shutdowns recorded by human reporters are frequently absent from automated measurement platforms and vice versa.

Abstract / §1 Introduction evaluation

Application-layer blocking — where censors restrict specific applications or services without disrupting IP connectivity — is invisible to network-level measurement systems like IODA that monitor BGP, active probing, darknet telescope, and Google Search traffic, making it a growing blind spot in automated shutdown detection.

Abstract / §3 Detection Gap Categories evaluation

AS-targeted shutdowns — where censors restrict connectivity at specific ISPs or autonomous systems rather than imposing country-wide outages — evade country-level aggregation in automated detection systems, which are calibrated to detect national-scope disruptions.

§3 Detection Gap Categories evaluation

The paper demonstrates that two protocol-specific censorship changes — QUIC blocking reaching 100% and DNS-over-TCP blocking reaching 96.68% — both occurred in the scan conducted immediately before Iran's June 18 full blackout, and that similar shutdown preparations were also documented before Iran's January 2026 shutdown. The authors hypothesize that continuous long-term measurement of protocol-specific censorship rates could provide advance warning of impending shutdowns before they come into full effect.

2026-anon-insights-into-iranian §3, §4 http3-quic-blockdns-poisoningmeasurement-platform

A code-level audit of 737 Chrome VPN and proxy browser extensions found that 520 of 522 sampled packages routed all non-loopback browsing traffic to a single shared SOCKS5 infrastructure; 274 of the 737 impersonated 66 known VPN or privacy brands across at least 40 developer accounts, and 516 of the identified extensions remained live in the Chrome Web Store at the time of data collection.

2026-anon-vpn-ai-deepseek §免费VPN扩展的核心问题 measurement-platform

Chrome Web Store metrics—including cumulative installation display counts totaling 75,486, five-star ratings, and brand-similar icons—provided no reliable signal of proxy operator trustworthiness among the 737 identified malicious VPN extensions; 516 remained listed throughout the study period despite routing traffic to a shared centralized infrastructure.

2026-anon-vpn-ai-deepseek §免费VPN扩展的核心问题 measurement-platform

Device-centric security analyses systematically underestimate user data exposure because backend infrastructure placement and jurisdictional context — not just on-device behavior — determine which actors can access sensitive data; a five-service geolocation ensemble (MaxMind, IPinfo, ip-api, DBIP, BGPView/RIPE) with CDN-aware attribution and WHOIS/BGP mapping was required to accurately characterize server-side risk.

2026-habib-empirical-study-backend Abstract measurement-platform

Three of the four active first-party sensitive-data endpoints in Pakistani government and telecom apps rely on domestic Pakistani infrastructure, identified via ASN and registry-level signals pointing to local administrative entities — placing identity credentials, location, and communication metadata within reach of Pakistani government administrative access.

2026-habib-empirical-study-backend Abstract measurement-platform

Across approximately 172 observed domains in 7 Pakistani government and telecom apps, only 4 active first-party endpoints handle highly sensitive data — including identity credentials, location information, and communication metadata — revealing extreme concentration of sensitive data flows into a small number of reachable endpoints.

2026-habib-empirical-study-backend Abstract measurement-platform