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Tracker

The “ISIC Tracker” uses computational methods to indentify anomalies in Tor usage.

Tracker below:

EXAMPLE:

[iframe src=”https://livedataoxford.shinyapps.io/OnlineLabourIndex/” width=”100% height=635]

Most Anomalous Countries by Tor Usage: 2020-03-29 (In order of median anomaly score over time period.)

Last Day

Bosnia & Herzegovina (BA)
Macedonia (MK)
Kyrgyzstan (KG)
Guyana (GY)
Cyprus (CY)
Peru (PE)
Azerbaijan (AZ)
Cambodia (KH)
Kazakhstan (KZ)
Egypt (EG)

Last Week

Armenia (AM)
Kyrgyzstan (KG)
Indonesia (ID)
Iran (IR)
Macedonia (MK)
Guyana (GY)
Mongolia (MN)
Azerbaijan (AZ)
Iraq (IQ)
Cambodia (KH)

Last 30 Days

Iran (IR)
Kyrgyzstan (KG)
Peru (PE)
Azerbaijan (AZ)
Guyana (GY)
Armenia (AM)
Lithuania (LT)
Venezuela (VE)
Indonesia (ID)
Macedonia (MK)

Overview of Tracker and Methodology

What is the ISIC Tor Tracker?

The ISIC Tor Tracker detects ongoing per-country anomalies in the daily usage metrics of the Tor anonymous communication network.

The tracker’s approach identifies contiguous anomalous periods, rather than daily spikes or drops, and allows anomalies to be ranked according to deviation from expected behaviour. The detection tool has been in developemnet since August 2016, and is in use by a number of individuals, academics, and NGOs as an early warning system for potential censorship events. While this tracker focusses on Tor, it’s approach is more generally applicable to usage data of other services, both individually and in combination. Future iterations of our tracker will look to combine multiple data sources which will allow more specific identification of likely Tor blocking events. If you wish to contribute to the development of this tracker please contact the ISIC Group at isis@oii.ox.ac.uk

Methodology & Academic Foundations

The “ISIC Tor Tracker” is based on the paper “On Identifying Anomalies in Tor Usage with Applications in Detecting Internet Censorship”^[1]

Stay Updated

If you wish to receive daily updates from the ISIC Tor Tracker, please revisit this webpage or sign up to the tracker’s mailing list.

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Footnotes

1. Joss Wright, Alexander Darer, and Oliver Farnan. 2018. On Identifying Anomalies in Tor Usage with Applications in Detecting Internet Censorship. In Proceedings of the 10th ACM Conference on Web Science (WebSci ’18). Association for Computing Machinery, New York, NY, USA, 87–96. https://doi.org/10.1145/3201064.3201093