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Record W4409592954 · doi:10.2514/1.i011583

High-Altitude Platform Station Systems Cybersecurity Analysis

2025· article· en· W4409592954 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

VenueJournal of Aerospace Information Systems · 2025
Typearticle
Languageen
FieldEngineering
TopicUAV Applications and Optimization
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPayload (computing)Computer securityComputer scienceArchitectureTransponder (aeronautics)Network architectureSystems architectureComputer networkEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

This paper examines cybersecurity threats in high-altitude platform station (HAPS) systems through reference architecture and attack tree methods. Given the rising commercial and military interest in these systems to enable next-generation 6G and hybrid telecommunication architectures, the threat of cyber and electronic attacks is increasing. The study focuses on providing the complete reference architecture of an aerostatic HAPS system equipped with a hybrid free-space optical and radio frequency transponder payload to be employed as a node of a nonterrestrial network. This study investigates potential attack vectors across various subsystems by coupling the attack tree methodology with the attack surface mapping derived from the reference architecture. Recommendations for mitigating cyberthreats and a secure-by-design approach are proposed to enhance the safety of future HAPS systems.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.210
Teacher spread0.205 · 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