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Record W6963305077 · doi:10.21227/6sjd-bv32

HITL UAV DoS GPS Spoofing Attacks (MAVLink)

2020· dataset· en· W6963305077 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE DataPort · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsAutopilotGlobal Positioning SystemFlight planSpoofing attackData collectionPlan (archaeology)Software

Abstract

fetched live from OpenAlex

Hardware-in-the-loop simulation of MAVLink UAV. Simulation environment follows standard jMAVSim setup (https://dev.px4.io/v1.9.0/en/simulation/hitl.html#jmavsimgazebo-hitl-environment).nbsp;Attacks are conducted against the UAV via serial connection. An autonomous survey flight is conducted over the University (~20min flight time). Full flight plan is located in the dataset package as OTU-Survey.plan.nbsp;PX4 Autopilot (https://px4.io)nbsp;running on Pixhawk 4 flight controller. QGroundControl used for GCS (http://qgroundcontrol.com)Telemetry data is contained in TLOG files (https://ardupilot.org/copter/docs/common-mission-planner-telemetry-logs.html)Full flight data is contained in ULOG files (https://dev.px4.io/v1.9.0/en/log/ulog_file_format.html)CSVs are extracted from TLOGs.nbsp;Examples of these attacks against the UAVs can be seen below (examples, not from recorded flights)Denial of Service:https://www.youtube.com/watch?v=npSBsSkWEHwGPS Spoofing:https://www.youtube.com/watch?v=Qw_Vo3FBw-cnbsp;

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.322
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0040.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.327

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.

Opus teacher head0.054
GPT teacher head0.320
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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