The paper offers insight on how Psiphon network data can be used to detect early signs of blocking.
In particular it describes the following the case studies of real events:
Iran: In 2017 & 2018 anti-government demonstrations arised and access to Telegram and Instagram was blocked in order to hinder protesters of organizing. Psiphon noticed an increase of uniques users and network bandwidth usage of 900% within the first week.
Iraq: In 2019 protests broke out and the government responded by censoring access to major social media platforms, messaging apps and even total internet shutdown in several cities. Subsequently, Psiphon connections for example from Baghdad were observed to drop from a rate of 500,000 connections per hour to zero across all ISPs.
Turkmenistan: In 2018 the only ISP in Turkmenistan initiated a crackdown on all VPNs by using a DPI filter. Over the next 30 days Psiphon noticed a consistent decrease of daily unique users and overall network bandwidth usage.
On the basis of these case studies, the authors indicate that periods of anomalous Psiphon usage can be used as early warning signs of censorship events.
Early Detection of Censorship Events with Psiphon Network Data Simin Kargar, Keith McManamen, Jacob Klein https://tics.site/proceedings/2019a/icn_2019_7_10_38005.pdf
The paper offers insight on how Psiphon network data can be used to detect early signs of blocking. In particular it describes the following the case studies of real events:
On the basis of these case studies, the authors indicate that periods of anomalous Psiphon usage can be used as early warning signs of censorship events.
Early Detection of Censorship Events with Psiphon Network Data was the subject of the Tor anti-censorship team's reading group on 2021-01-21. A transcript of the session including a discussion with one of the authors, Keith McManamen, can be found here: http://meetbot.debian.net/tor-meeting/2021/tor-meeting.2021-01-21-15.58.log.html#l-175