A Survey and Taxonomy Aimed at the Detection and Measurement of Covert Channels
Bibliographic record
Abstract
New viewpoints of covert channels are presented in this work. First, the origin of covert channels is traced back to acc ess control and a new class of covert channel, air-gap covert channels, is presented. Second, we study the design of covert channels and provide novel insights that differentiate the research area of undetectable communication from that of covert channels. Third, we argue that secure systems can be characterized as fixed-source systems or continuous-source systems, i.e., systems whose security is compromised if their design allows a covert channel to communicate a small, fixed amount of information or communicate information at a sufficiently high, continuous rate, respectively. Consequently, we challenge the traditional method for measuring covert channels, which is based on Shannon capacity, and propose that a new measure, steganographic capacity, be used to accurately assess the risk posed by covert channels, particularly those affecting fixed-source systems. Additionally, our comprehensive review of covert channels has led us to the conclusion that important properties of covert channels have not been captured in previous taxonomies. We, therefore, present novel extensions to existing taxonomies to more accurately characterize covert channels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.012 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".