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Record W4411666642 · doi:10.34190/eccws.24.1.3333

Cyber Defence Trainer for Marine Integrated Platform Management Systems

2025· article· en· W4411666642 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

VenueEuropean Conference on Cyber Warfare and Security · 2025
Typearticle
Languageen
FieldEngineering
TopicMilitary Strategy and Technology
Canadian institutionsRoyal Canadian NavyRoyal Military College of Canada
Fundersnot available
KeywordsTrainerSystems engineeringComputer scienceBusinessEngineeringComputer securityProcess managementOperating system

Abstract

fetched live from OpenAlex

Modern civilian and military marine vessels employ integrated platform management systems to monitor and control various different operational ship systems such has engine control, navigation and potentially weapon systems. These platform management systems consist of information and operational technology (IT/OT) environments that integrate commercial operating systems, TCP/IP based protocols and supervisory control and data acquisition (SCADA) systems in order to monitor and control marine cyber physical systems. This integration of technologies introduces threat vectors as well as unique operational, safety and potentially environmental impacts for marine vessels. Ships’ crews do not always have security monitoring capabilities and trained security staff who understand the various onboard systems to the extent they could detect a cyber attack. Furthermore, there is a lack of training environments that could be used to educate marine cyber operators. The aim of this research is to build an environment based on effective cyber training techniques to enable the education of marine cyber operators in defensive cyber operations. The environment in this context is a defensive cyber security trainer that enables students to analyse network traffic in order to detect attacks against any ship systems, including cyber physical systems. Effective training techniques refers to the pedagogical recommendations for successful cyber education and effective gamified design. Educating marine cyber operators how to detect attacks on marine IT/OT environments within an integrated platform management system will enable better protection from cyber attack against marine vessels. To accomplish this aim, defensive cyber trainer was developed that consisted of three key components. The first was a Capture the Flag (CTF) framework. The second was a server that included the emulation and simulation of key ship integrated platform management system components within a virtualized environment. Third, were open source and customized plugins used to analyse traffic in our virtualized ship and the inclusion of three different kill chains based on real attacker tactics, techniques and procedures (TTPs). This defensive cyber trainer was validated against research methodologies for effective gamified environment design.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.852
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.226
Teacher spread0.206 · 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