Machine Relations Index

AI Security & Privacy · Machine Relations Index category

Which sources AI engines cite for AI Security & Privacy questions

Vendor-owned sources earn 41.3% of classified citations in AI Security & Privacy answers (1,701 of 4,116), as of November 2, 2026.

In the November 2026 release of the Machine Relations Index, these are the sources AI answer engines cited most often for each of the 6 AI Security & Privacy question shapes, each ranked on that shape's own observed runs. This category has 6 observed question-shape segments in the current public release. Each segment keeps its own observed-run denominator and dates; this page does not average rates across shapes. Observed runs are answer runs, not questions: every segment repeats a small set of distinct questions across engines and dates, so a run count is not a count of independent questions.

Top sources by question shape

The sources engines cite most, shape by shape

A rate is the share of the shape's observed answer runs that cited the source; rank is the source's place on that shape's full leaderboard.

Best tools

Example pattern: best AI security privacy tools. 298 observed runs across 13 dates.

RankSourceSource roleCitation rateCited runs
#1 of 448Arxiv.orgAcademic and government source34.23%102 of 298
#2 of 448Getmaxim.aiOther observed source26.85%80 of 298
#3 of 448Futureagi.comOther observed source17.79%53 of 298
#4 of 448MediumCommunity and social platform17.11%51 of 298
#5 of 448Amazon.comOther observed source14.09%42 of 298

Full Best tools leaderboard, 448 sources

How buyers choose

Example pattern: how to choose AI security privacy tools. 294 observed runs across 13 dates.

RankSourceSource roleCitation rateCited runs
#1 of 477Teramind.coOther observed source18.71%55 of 294
#2 of 477Philterd.aiOther observed source16.67%49 of 294
#3 of 477Arxiv.orgAcademic and government source13.61%40 of 294
#4 of 477Strac.ioVendor-owned source11.90%35 of 294
#5 of 477Aona.aiOther observed source11.56%34 of 294

Full How buyers choose leaderboard, 477 sources

Is it worth it

Example pattern: is AI security privacy software worth it. 294 observed runs across 13 dates.

RankSourceSource roleCitation rateCited runs
#1 of 527Ovaledge.comOther observed source17.35%51 of 294
#2 of 527Witness.aiOther observed source14.97%44 of 294
#3 of 527Veeam.comOther observed source11.22%33 of 294
#4 of 527Radware.comOther observed source10.88%32 of 294
#5 of 527Cloudflare.comOther observed source9.52%28 of 294

Full Is it worth it leaderboard, 527 sources

Problem-first research

Example pattern: how to solve AI security privacy problems. 277 observed runs across 13 dates.

RankSourceSource roleCitation rateCited runs
#1 of 513TechRadarEditorial publication12.27%34 of 277
#2 of 513Arxiv.orgAcademic and government source11.91%33 of 277
#3 of 513Conferbot.comOther observed source10.83%30 of 277
#4 of 513TechTargetEditorial publication9.75%27 of 277
#5 of 513LinkedInCommunity and social platform8.66%24 of 277

Full Problem-first research leaderboard, 513 sources

Top lists

Example pattern: top AI security privacy platforms. 275 observed runs across 13 dates.

RankSourceSource roleCitation rateCited runs
#1 of 472Arxiv.orgAcademic and government source27.64%76 of 275
#2 of 472Ovaledge.comOther observed source23.27%64 of 275
#3 of 472Osano.comOther observed source17.09%47 of 275
#4 of 472Github.comCommunity and social platform16.73%46 of 275
#5 of 472Ketch.comVendor-owned source16.73%46 of 275

Full Top lists leaderboard, 472 sources

Comparisons

Example pattern: AI security privacy platform A vs B. 283 observed runs across 13 dates.

RankSourceSource roleCitation rateCited runs
#1 of 391Arxiv.orgAcademic and government source39.22%111 of 283
#2 of 391MediumCommunity and social platform16.61%47 of 283
#3 of 391Apxml.comOther observed source13.43%38 of 283
#4 of 391Nhimg.orgOther observed source9.19%26 of 283
#5 of 391YouTubeSearch or media platform8.48%24 of 283

Full Comparisons leaderboard, 391 sources

Observed shapes6

Canonical segment URLs exist only for observed category/shape pairs.

Published6

Published segments met the release evidence floor.

Collecting0

Collecting segments expose sample progress, not mature leaderboards.

ReleaseNovember 2, 2026

Methodology v2.1.

Question shapes

Separate denominators by segment

Question shapeStateObserved runsDistinct questionsRun datesDistinct cited domainsCanonical segment
Best toolsPublished2987 (5 paraphrase groups)13448Open leaderboard
How buyers choosePublished2947 (5 paraphrase groups)13477Open leaderboard
Is it worth itPublished2947 (5 paraphrase groups)13527Open leaderboard
Problem-first researchPublished2777 (5 paraphrase groups)13513Open leaderboard
Top listsPublished2757 (5 paraphrase groups)13472Open leaderboard
ComparisonsPublished2837 (5 paraphrase groups)13391Open leaderboard

By answer engine

Whole-window rates on each engine

Each link ranks sources with a published AI Security & Privacy segment by that source's citation rate on one engine across the whole window. It is not a rate inside AI Security & Privacy alone. A collecting engine has no published ranking for this category.
Cite this
Citation
Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. AI Security & Privacy, observed Machine Relations Index category, 2026-05-10 to 2026-11-02. Release mri_score_v2.1+2026-11-02+f9aaeca0db15. https://machinerelations.ai/index/categories/ai-security-privacy. CC BY 4.0.
APA
Parrott, J. (2026). AI Security & Privacy in the Machine Relations Index (Version mri_score_v2.1+2026-11-02+f9aaeca0db15) [Data set]. Machine Relations Research. https://machinerelations.ai/index/categories/ai-security-privacy https://doi.org/10.5281/zenodo.23652423
BibTeX
@misc{parrott2026mriaisecurityprivacy,
  author = {Parrott, Jaxon},
  title = {AI Security \& Privacy in the Machine Relations Index},
  year = {2026},
  version = {mri\_score\_v2.1+2026-11-02+f9aaeca0db15},
  publisher = {Machine Relations Research},
  url = {https://machinerelations.ai/index/categories/ai-security-privacy},
  doi = {10.5281/zenodo.23652423},
  license = {CC-BY-4.0},
  note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai}
}

CITATION.cff

Release and boundary

No pooled category score

Published November 2, 2026. The observation window runs May 10, 2026 to November 2, 2026. Methodology v2.1.

Use the data
curl -fsSL "https://machinerelations.ai/data/machine-relations-index.json" -o machine-relations-index.json
curl -fsSL "https://machinerelations.ai/data/mri-release-manifest.json" -o mri-release-manifest.json
curl -fsSL "https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv" -o domains.csv
curl -fsSL -L "https://doi.org/10.5281/zenodo.23652423" -o mri-zenodo.html
import json
from urllib.request import urlopen

index_url = "https://machinerelations.ai/data/machine-relations-index.json"
with urlopen(index_url) as response:
    index = json.load(response)
print(index["generated"], index["total_domains"])

This page is a directory of observed segments. A domain's overall citation rate is not a category rate, and MRI does not publish an averaged category score in this slice.

AI Security & Privacy buyers on AuthorityTech’s publication intelligence is a downstream practitioner projection of these segments. It is not source evidence, citation provenance, or an identity link for the neutral dataset.