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Record W2473397309 · doi:10.1145/2938370

Out-of-Band Covert Channels—A Survey

2016· review· en· W2473397309 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

VenueACM Computing Surveys · 2016
Typereview
Languageen
FieldComputer Science
TopicInternet Traffic Analysis and Secure E-voting
Canadian institutionsUniversity of Ottawa
FundersU.S. Department of Defense
KeywordsCovertCovert channelAdversaryComputer scienceAdversarial systemChannel (broadcasting)Computer securityAdversary modelTheoretical computer scienceArtificial intelligenceTelecommunicationsLinguistics

Abstract

fetched live from OpenAlex

A novel class of covert channel, out-of-band covert channels, is presented by extending Simmons’ prisoners’ problem . This new class of covert channel is established by surveying the existing covert channel, device-pairing, and side-channel research. Terminology as well as a taxonomy for out-of-band covert channels is also given. Additionally, a more comprehensive adversarial model based on a knowledgeable passive adversary and a capable active adversary is proposed in place of the current adversarial model, which relies on an oblivious passive adversary. Last, general protection mechanisms are presented, and an argument for a general measure of “covertness” to effectively compare covert channels is given.

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)0.012
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0050.002
Research integrity0.0000.001
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 head0.079
GPT teacher head0.332
Teacher spread0.253 · 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