The DOI matches its Crossref record, with a small difference in title or year; 62 of the 65 references it cites were found in a registry or an index.
Censored Planet: An Internet-wide, Longitudinal Censorship Observatory
Open accessAbstract
Remote censorship measurement techniques offer capabilities for monitoring Internet reachability around the world. However, operating these techniques continuously is labor-intensive and requires specialized knowledge and synchronization, leading to limited adoption. In this paper, we introduce Censored Planet, an online censorship measurement platform that collects and analyzes measurements from ongoing deployments of four remote measurement techniques (Augur, Satellite/Iris, Quack, and Hyperquack). Censored Planet adopts a modular design that supports synchronized baseline measurements on six Internet protocols as well as customized measurements that target specific countries and websites. Censored Planet has already collected and published more than 21.8 billion data points of longitudinal network observations over 20 months of operation. Censored Planet complements existing censorship measurement platforms such as OONI and ICLab by offering increased scale, coverage, and continuity. We introduce a new representative censorship metric and show how time series analysis can be applied to Censored Planet's longitudinal measurements to detect 15 prominent censorship events, two-thirds of which have not been reported previously. Using trend analysis, we find increasing censorship activity in more than 100 countries, and we identify 11 categories of websites facing increasing censorship, including provocative attire, human rights issues, and news media. We hope that the continued publication of Censored Planet data helps counter the proliferation of growing restrictions to online freedom.
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“First, the timing of censorship during a coup is consistent with many studies that have shown that Internet censorship is targeted during sensitive political time periods and periods of potential power transitions, such as elections and large-scale protests [23,25,44,47,73].”
From A multi-perspective view of Internet censorship in Myanmar (2021) · cites this paper as [73]
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Faulkenberry, A., Avgetidis, A., Alrawi, O., Ma, Z., Perdisci, R., & Antonakakis, M. (2026) · IEEE European Symposium on Security and Privacy · doi:10.1109/eurosp68448.2026.00057
A Survey and Taxonomy of Internet Censorship Methods
Master, A., & Spafford, E. H. (2026) · Computers & Security · doi:10.1016/j.cose.2026.105076
Künzig, F., Vollhardt, K., Paß, M., Generalova, S., Kaiser, C., Nowack, S., Ververis, V., & Bajpai, V. (2026) · Network Traffic Measurement and Analysis Conference (TMA) · doi:10.23919/tma71232.2026.11695494
Metadata
- Authors
- Sundara Raman, R., Shenoy, P., Kohls, K., & Ensafi, R.
- Affiliations
- University of Michigan, Ann Arbor, MI, USA
- University of Michigan (US)
- Ruhr University Bochum (DE)
- Venue
- Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security
- Publisher
- ACM
- Published
- 2020-10-30
- Pages
- 49-66
- ISSN
- 1543-7221 (ISSN-L)
- OpenAlex
- W3110509121
- Cited by
- 75
- References
- 65
- Citations by year
- 2026: 11 · 2025: 13 · 2024: 13 · 2023: 14 · 2022: 9 · 2021: 12 · 2020: 3
- FWCI
- 3.62
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- ACM SIGSAC Conference on Computer and Communications Security (CCS) (publishedVersion, cc-by)
- Funders
- National Science Foundation (CNS-1755841)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Internet Traffic Analysis and Secure E-voting
- Social Sciences › Law › Freedom of Expression and Defamation
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Keywords
- internet censorship, remote measurement, Augur, charlatans, internet freedom, time series analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.