ITHI by ICANN | Full table | |
---|---|---|
Identifier Technology Health Indicator | - | |
% No Such Domain queries seen by root servers | - | |
% of resolvers that perform DNSSEC validation | - | |
%requests to top name at the root | - | - |
%requests to top name at resolvers | - | - |
Number of resolvers seeing 50% of first queries | - | |
Phishing Domains per 10,000 registered names | - |
In 2017, ICANN started a project to monitor the health of the registered identifiers ecosystem, through a set of Identifier Technology Health Indicators (ITHI), or ITHI Metrics. There are eight detailed metrics for which data can be seen on this site. The metrics are computed using data captured from various sources including data collected by ICANN projects and traces obtained from participating root DNS servers, authoritative DNS servers, and recursive DNS resolvers. Our first data collection partners are:
The table above presents our top 5 indicators. The table below presents a bigger list, with more details.
ITHI by ICANN | Identifier Technology Health Indicator | - | Past 3 months | Historic Low | Historic High | |
---|---|---|---|---|---|---|
Root Server Health | % No Such Domain queries seen by root servers | - | - | - | - | |
DNSSEC Deployment | % of resolvers that perform DNSSEC validation | - | - | - | - | |
Name collision | %requests to top 3 names at the root | - | - | - | - | - |
- | - | - | - | - | ||
- | - | - | - | - | ||
%requests to top 3 names at resolvers | - | - | - | - | - | |
- | - | - | - | - | ||
- | - | - | - | - | ||
Resolver Concentration | Number of resolvers seeing 50% of first queries | - | - | - | - | |
Number of resolvers seeing 90% of first queries | - | - | - | - | ||
DNS Abuse | Abuse Domains per 10,000 registered names | Phishing | - | - | - | - |
Malware | - | - | - | - | ||
Botnets C&C | - | - | - | - | ||
Spam | - | - | - | - | ||
Number of GTLD to account for 50% of abuses | Phishing | - | - | - | - | |
Malware | - | - | - | - | ||
Botnets C&C | - | - | - | - | ||
Spam | - | - | - | - | ||
Number of GTLD to account for 90% of abuses | Phishing | - | - | - | - | |
Malware | - | - | - | - | ||
Botnets C&C | - | - | - | - | ||
Spam | - | - | - | - |