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Pavlos Sermpezis is a researcher at Datalab (datalab.csd.auth.gr), Aristotle University of Thessaloniki, Greece. His research is mainly on data science, Internet routing and measurements.
• 11 min read
This article presents a set of open-source tools - “reusable visualisations” - that extend the AS hegemony visualisations provided by the Internet Health Report. Users can directly use the online tools or embed the IHR data on their own posts, webpages, or Observable HQ notebooks.
• 9 min read
BGP prefix hijacking is a persistent threat against Internet organisations, attributed to a lack of authorisation and authentication mechanisms in the inter-domain routing system. ARTEMIS (Automatic and Real-Time dEtection and MItigation System) is a defence system against BGP prefix hijacking, whi…
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“Unless I'm wrong, the bias for RIPE Atlas probes is measured by the number of probes in the AS. Isn't there also a bias when asking N probes for a measurement, without specifying area/country/AS? Are we guaranteed that the set of probes we obtain respects the general population of probes? Or is there an extra bias here?”
Thanks Stéphane for bringing this up! The bias for RIPE Atlas shown in the plots corresponds to the entire set of RIPE Atlas probes (i.e., if someone did measurements using all the 11k probes, he/she would have this bias). When asking only N probes for measurements, which is what happens in practice, the bias we have is higher. The smaller the number of probes N, the higher the bias. You can see some preliminary results/visuals on this (i.e., number of probes N vs bias) at this readme page https://github.com/sermpezis/ai4netmon/blob/main/use_cases/bias_in_monitoring_infrastructure/Bias_vs_sampling.md on our project's github
Thanks @Gergana and @RACI! For those interested in the AI4NetMon project, more info can be found in the project website https://sermpezis.github.io/ai4netmon/ . Feel free to contact us for more info or collaboration
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