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Detecting a Crisis: Comparison of Self-Reported vs. Automated Internet Outage Measuring Methods

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Gesellschaft für Informatik e.V.


Every day, there are internet disruptions or outages around the world that affect our daily lives. In this paper, we analyzed these events in Germany in recent years and found out how they can be detected, and what impact they have on citizens, especially in crisis situations. For this purpose, we take a look at two different approaches to recording internet outages, namely the self-reporting of citizens and automatic reporting by algorithmic examination of the availability of IP networks. We evaluate the data of six major events with regard to their meaningfulness in quality and quantity. We found that due to the amount of data and the inherent imprecision of the methods used, it is difficult to detect outages through algorithmic examination. But once an event is publicly known by self-reporting, they have advantages to capture the temporal and spatial dimensions of the outage due to its nature of objective measurements. As a result, we propose that users’ crowdsourcing can enhance the detection of outages and should be seen as an important starting point to even begin an analysis with algorithm-based techniques, but it is to ISPs and regulatory authorities to support that.


Orlov, Denis; Möller, Simon; Düfer, Sven; Haesler, Steffen; Reuter, Christian (2022): Detecting a Crisis: Comparison of Self-Reported vs. Automated Internet Outage Measuring Methods. Mensch und Computer 2022 - Workshopband. DOI: 10.18420/muc2022-mci-ws10-321. Bonn: Gesellschaft für Informatik e.V.. MCI-WS10: 9. Workshop Mensch-Maschine-Interaktion in sicherheitskritischen Systemen. Darmstadt. 4.-7. September 2022