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Record W1994628740 · doi:10.4018/jte.2011040105

Socio-Technical Influences of Cyber Espionage

2011· article· en· W1994628740 on OpenAlexaff
Xue Lin, Rocci Luppicini

Bibliographic record

VenueInternational Journal of Technoethics · 2011
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEspionagePoliticsCounterintelligenceIndustrial espionageVariety (cybernetics)Government (linguistics)Political scienceDocumentationPublic relationsSociologyLaw

Abstract

fetched live from OpenAlex

Technoethical inquiry deals with a variety of social, legal, cultural, economic, political, and ethical implications of new technological applications which can threaten important aspects of contemporary life and society. GhostNet is a large-scale cyber espionage network which has infiltrated important political, economic, and media institutions including embassies, foreign ministries and other government offices in 103 countries and infected at least 1,295 computers. The following case study explores the influences of GhostNet on affected organizations by critically reviewing GhostNet documentation and relevant literature on cyber espionage. The research delves into the socio-technical aspects of cyber espionage through a case study of GhostNet. Drawing on Actor Network Theory (ANT), the research examined key socio-technical relations of Ghostnet and their influence on affected organizations. Implications of these findings for the phenomenon of GhostNet are discussed in the hope of raising awareness about the importance of understanding the dynamics of socio-technical relations of cyber-espionage within organizations.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.040
GPT teacher head0.309
Teacher spread0.269 · 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 designTheoretical or conceptual
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

Citations2
Published2011
Admission routes1
Has abstractyes

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