A Strong Three-Factor Authentication Device: Trusted DAVE and the New Generic Content-Based Information Security (CBIS) Architecture
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.
Bibliographic record
Abstract
This report has three objectives. The first objective is to provide a description/analysis of the Trusted DAVE activity performed by DRDC Ottawa and its contractors. The second is to describe different systems where the demonstrator produced under this activity could be used. The last is to analyse, study, and compare different types of network/system architectures. The activity involved the development of three elements: A secure design for a three-factor Trusted Device for Authentication and VErification (Trusted DAVE), a device demonstrator implementing some of those design elements, and an authentication and verification demonstration system that utilises the device demonstrator. The purpose of the device is to provide the user interface component to be used as a part of a strong Verification and Authentication (V&A) capability for systems used to process classified or sensitive data. Four possible systems that could use Trusted DAVE are presented. Two of them are related to the CBIS (Content-Based Information Security) concepts and one integrates CBIS and Kerberos. Finally, three architectures for network systems are presented with their advantages and their limitations. A Generic CBIS architecture covering the one specified in the US CBIS ACTD is defined and compared with the two others. The purpose of the Generic CBIS architecture is threefold: (1) provide an architecture for systems generalizing the US ACTD one, (2) illustrate the architecture's fundamental aspects, and (3) introduce an architecture where Trusted DAVE could be useful.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it