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Complete runnable SecJev checkpoint for jev-stageA JEV defense
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Sources and attribution

SecJev-Corpus v1.0.0 transforms upstream observations into structured decision questions. Transformations include feature projection, identifier anonymization, history-window construction, explicit-policy labeling, deduplication, option permutation, and grouped splitting. Source annotations are not relabeled as proven real-world attacks. Newly run simulations are identified as SecJev experiments rather than results reported by the upstream authors.

CICIoT2023 — 48,000 questions

E. C. P. Neto, S. Dadkhah, R. Ferreira, A. Zohourian, R. Lu, and A. A. Ghorbani. CICIoT2023: A real-time dataset and benchmark for large-scale attacks in IoT environment (2023).

CIC explicitly permits redistribution and mirroring with dataset and paper attribution. Capture labels remain capture-level annotations; incidental background traffic is possible.

ToN-IoT — 40,000 questions

Official dataset and usage conditions. Free academic research use is granted by the authors; commercial use requires separate author permission. The source requests citation of the following eight publications, linked from its official page:

  1. Nour Moustafa (2021), network dataset study, Sustainable Cities and Society, 102994.
  2. Tim M. Booij, Irina Chiscop, Erik Meeuwissen, Nour Moustafa, and Frank T. H. den Hartog (2021), ToN-IoT heterogeneity and feature standardization, IEEE Internet of Things Journal.
  3. Abdullah Alsaedi, Nour Moustafa, Zahir Tari, Abdun Mahmood, and Adnan Anwar (2020), TON-IoT telemetry dataset, IEEE Access 8, 165130–165150.
  4. Nour Moustafa, M. Keshk, E. Debie, and H. Janicke (2020), federated Windows datasets, TrustCom, 848–855. DOI: 10.1109/TrustCom50675.2020.00114.
  5. Nour Moustafa, M. Ahmed, and S. Ahmed (2020), ToN-IoT Linux dataset evaluation, TrustCom, 727–735. DOI: 10.1109/TrustCom50675.2020.00100.
  6. Nour Moustafa (2019), TON-IoT dataset presentation, eResearch Australasia.
  7. Nour Moustafa (2019), IoT–Fog–Cloud architecture review. arXiv:1906.01055.
  8. Javed Ashraf et al. (2021), IoTBoT-IDS, Sustainable Cities and Society, 103041.

Mirror used: codymlewis/TON_IoT_network, revision b953d9388d2db3bc392ea7150476e4f219a2a1cb. Features derive from the fixed network CSV.

VeReMi NextGen — 22,498 questions

Artur Hermann, Jan-Niklas Remmers, Dennis Eisermann, Benjamin Erb, and Frank Kargl. VeReMi NextGen: A Dataset for Evaluating Misbehavior Detection Systems in VANETs. Zenodo record / DOI 10.5281/zenodo.19665762. License: CC BY 4.0; full notice in licenses/VeReMi-LICENSE.txt.

Only validated observation categories enter this corpus. Sender claims are projected into a common representation. The official independent test boundary is retained.

Twins / Streamlet — 29,588 questions

Twins simulator, revision 3a3215addf3f79cb7b1dd2b0677f4d0896943d0b; Apache-2.0 notice included. These are newly sampled controlled experiments using the upstream implementation. Answers follow the explicit observer certificate policy and visible message history. A validator ID follows the simulator's physical-author representation; no hidden attacker identity is inferred.

ByzFL / FoolsGold / MNIST — 17,000 questions

  • ByzFL, EPFL, revision 5830978d991a0900748f7ce901dc3ca532081b26; MIT.
  • FoolsGold, revision 0aa55114296a2d3c2bcb6f544a6fae31e8e7b8b4; MIT.
  • Yann LeCun, Corinna Cortes, and Christopher J. C. Burges, MNIST handwritten-digit data, underlying the controlled gradient experiments.

The corpus contains measured update summaries from 80 fresh runs, with separate MNIST pools across splits and explicit attacker configurations. Original images are not redistributed. The earlier simulated aggregation-selection tasks are not part of this release.

LANL — 7,902 questions

Alexander D. Kent (2015), Comprehensive, Multi-Source Cyber-Security Events. Los Alamos National Laboratory. DOI: 10.17021/1179829. Related publication: A. D. Kent, Cybersecurity Data Sources for Dynamic Network Research, in Dynamic Networks in Cybersecurity, 2015.

Official data, citation and public-domain dedication. Our questions use visible authentication histories and explicit triage rules. Unlabeled events are not assigned a confirmed-benign label. The source's successful-authentication selection bias remains applicable.

AgentDojo — 4,143 questions

AgentDojo, ETH Zurich SPY Lab and contributors, revision 089ed468cf3ed0322acc66b0211f26d9d90dbf60; MIT notice included. Records are drawn from published tool outputs and attack/control runs. Task and shared-response components are grouped; shared environment or attack templates are not a claim of unseen-template evaluation.

InjecAgent — 1,054 questions

InjecAgent, UIUC Kang Lab and contributors, revision f19c9f2c79a41046eb13c03c51a24c567a8ffa07; MIT notice included. This release uses the declared objectives of injected instructions. The all-positive injection-detection task is excluded.