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Record W4411666649 · doi:10.34190/eccws.24.1.3380

CyberX 2.0: From Hacks to Head Games - Evolving Cyber Defence with Strategic Twists and Tactical Consequences

2025· article· en· W4411666649 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
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsHead (geology)Computer securityComputer scienceGeology

Abstract

fetched live from OpenAlex

CyberX is a unique, large-scale cyber operations exercise that incorporates a cyber-kinetic battlespace, designed to provide participants with a realistic, multifaceted problem space. The original environment offered limited support for Information Environment operations beyond scenarios for Defensive Cyber Operations, Offensive Cyber Operations, and Computer Network Exploitation. These scenarios did not initially include aspects of information operations or cognitive influence, such as diplomacy, propaganda, fake news, social media manipulation, and political subversion—key elements associated with hybrid warfare. This paper presents the ongoing evolution of CyberX, which introduces new dimensions of Information Operations to enhance the exercise scenarios and broaden learning opportunities for participants. The goal is to incorporate open-source intelligence and cognitive influence elements into Information Environment operations. New features include a geopolitical context for the mission scenario and a cognitive dimension to the Information Environment, ensuring that decisions made at the tactical cyberspace level carry real consequences. An integrated social media environment now supports Information Operations scenarios, populated by simulated personas and social media interactions. Exercise control referees use this platform to set up the scenario and manage gameplay. The platform leverages AI to semi-automatically generate message content, blending AI-generated rumors with ground-truth information. This simulated information space provides commanders with a more nuanced understanding of adversary disposition and movements. However, with this enhanced insight comes a greater strategic responsibility, requiring commanders to operate within the cognitive geopolitical space. This evolution makes the CyberX mission scenarios more tangible and realistic. The goal is to ensure that decisions made at the tactical cyberspace layer have real consequences. Choices aimed at locally optimizing risk in response to a cyber threat at the expense of overall mission success are discouraged. The learning outcomes now emphasize the integrated nature of cyber operations with other operational domains and their interdependence for mission success.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score1.000

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 communication0.0010.001
Open science0.0010.000
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 head0.030
GPT teacher head0.270
Teacher spread0.240 · 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