GithuBarry / DNSSEC-Stats

Use DNSVIZ to measure DNSSEC deployment and produce statistics on generated warnings.

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DNSSEC-Stats

Use DNSVIZ to measure DNSSEC deployment and produce statistics on generated warnings.

We use top top-1m.csv ranking from https://statvoo.com/dl/top-1million-sites.csv.zip. Data retrived on Dec. 20, 2020. From it, we generated top10000.csv.

We tested on authoritative DNS servers and recursive servers including 1.1.1.1, 8.8.8.8, 114.114.114.114, and 223.5.5.5. We ran all probes on a Linode in Fremont, CA, United States. The experiment was carried out in Dec. 20, 2020 - Jan. 5, 2021.

Outcomes JSONs

To see our final outcomes, go to any folder under Linode Results and find files named as results_*.json. These files include results of running DNSSEC analysis of top10000.csv (but not including domains listed in probe_actual_failures.txt in the same folder).

(e.g. See warning stats for Cloudfare DNS or the complete results on domains in our top10000.csv except these failed domains).

Among the 10000 domains we probed, each recursive DNS server fails <50 domains, but in the authoritative case we failed to probe 482 domains.

To understand an error code, try exact search of the code at DNSVIZ error script.

Workflow used

Our workflow includes 1) gathering probe data 2) generate reports on warnings 3) clean up 4) produce data. This procedure can be seen in any folder inLinode Results.

In the authorative case, we further run delegation status analyzer and its clean up procedures.

Raw probe data zips

In Linode, I copied the same python working directory multiple times when testing different data and I zip them as a back up of our probe data. These zip files are in Linode Results Zips. Most of the zip files contains only the probing data (so only 1st step) without later analysis and can be a bit messy. Note that Linode Results have renamed and new running scripts and thus more clear than those in the zips (e.g. clean up script was not included in zips).

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Use DNSVIZ to measure DNSSEC deployment and produce statistics on generated warnings.