Artificial Intelligence f or Cybersecurity in IoT-enabled Avionics: Challenges and Solutions
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.
Bibliographic record
Abstract
Implementing Internet of Things (IoT)-based services in commercial aviation gives a painless and effortless experience to passengers and crew members, but the mitigation of cyber-attacks is challenging. Available solutions are not enough to overcome various cyber security attacks. Hence, we need more attention to overcome the challenges and cyber risks in commercial aviation. The aim of this paper is to highlight the various factors of cyber threat in avionics and discuss the major security studies conducted to date. The goal is to layout the ground for an insightful discussion about Artificial Intelligence (AI) potential, challenges, and solutions for cybersecurity in avionics. We will focus on how AI and IoT can be used to identify cyber security threats, type of attacks, and infrastructure vulnerabilities. This information will help us in developing effective preventive measures in the future.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it