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Record W2512352309 · doi:10.5539/mas.v10n11p159

A CTF-Based Approach in Information Security Education: An Extracurricular Activity in Teaching Students at Altai State University, Russia

2016· article· en· W2512352309 on OpenAlexvenueno aff
Alexander Mansurov

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsnot available
Fundersnot available
KeywordsClubComputer scienceState (computer science)Mathematics educationPsychology

Abstract

fetched live from OpenAlex

Capture the Flag (CTF) competitions are the most popular events in cybersecurity conferences where participants can demonstrate their skills. Also, the CTF is widely acknowledged as a valuable pedagogical tool for providing the students with real life problems in computer security area when dealing with CTF tasks. However, there is the possibility to go beyond treating CTF tasks only. The paper presents an approach to establish a CTF-based educational framework that allows students to gain more practical skills, knowledge and expertise in information security and related areas. The framework is implemented in Altai State University (Barnaul, Russia) in 2014 as an extracurricular club activity, and the club runs successfully up till now. Pedagogical benefits, learning methodology and educational aspects are discussed, and positive feedback shows the success of the proposed approach.

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.

How this classification was reachedexpand

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.006
Open science0.0020.001
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 head0.007
GPT teacher head0.239
Teacher spread0.231 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2016
Admission routes1
Has abstractyes

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