Comparative Analysis of DoT and HTTPS Certificate Ecosystems
Bibliographic record
Abstract
Systemd-resolved", among others, have implemented DoT stub-resolvers [16].As a result, DoT queries have increased over the Internet since 2018 [27].Similar to securing web (HTTPS) and email (S/MIME), DoT in the Internet relies on the Internet's Public Key Infrastructure (PKI) and associated Certification Authorities (CAs) for signing and delivering resolvers' standard X.509 certificates.On security, we investigate whether DoT would be susceptible to classic (or historic) PKI shortcomings, such as invalid/self-signed certificates, weak cryptographic parameters, or fraudulent certificates issued by compromised CAs.Over time, browsers enhanced HTTPS security by stringent certificate validation and indispensable demand of security features, like the placement of certificates in Certificate Transparency (CT) logs [38], [6]; CAs have accordingly been steppingup their issuance standards.It is unclear how many of the browser-implemented reinforcements for HTTPS are adopted in DoT, and how the relatively lax security in DoT affects issued certificates.For example, successful authentication [4] and encryption are unnecessary in DoT depending on the client's configured usage profile (see opportunistic mode in RFC 7858 [42]).We present results upon comparing a random sample of DoT and HTTPS certificates collected from Rapid7 [32].Particularly, this paper contributes results upon comparing DoT and HTTPS certificates for the following aspects: Distribution and characteristics of certificate issuers (Sec.IV).Certificate parameters, including validity windows and cipher-suites (Sec.V).Proportion and distribution of certificates in CT-logs (Sec.VI).Our results highlight non-major differences between both ecosystems, including differences in: the dominant CA, certificate validity, and cryptographic properties.The proportion of invalid certificates appears almost similar in both ecosystems, likewise the expiry windows and cryptographic functions.We also found almost equivalent rates of CT-log inclusion in both ecosystems.These results suggest that so far, the deployment and usage of DoT certificates in practice appears promising, and not significantly affected by the lack of strict security checks in sub-resolvers.Abstract-The Internet's Public Key Infrastructure (PKI) has been used to provide security to HTTPS and other protocols over the Internet.Such infrastructure began to be increasingly relied upon for DNS security.DNS-over-TLS (DoT) is one recent rising and prominent example, whereby DNS traffic between stub and recursive resolver gets transmitted over a TLS-secured session.The security research community has studied and improved security shortcomings in the web certificate ecosystem.DoT's certificates, on the other hand, have not been investigated comprehensively.It is also unclear if DoT client-side tools (e.g., stub resolvers) enforce security properly as modern-day browsers and mail clients do for HTTPS and secure email.In this research, we compare the DoT and HTTPS certificate ecosystems.Preliminary results are so far promising, as they show that DoT appears to have benefited from the PKI security advancements that were mostly tailored to HTTPS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".