A review and comparative evaluation of forensics guidelines of NIST SP 800-101 Rev.1:2014 and ISO/IEC 27037:2012
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
In this paper, we present a review and comparative evaluation of forensics guidelines of NIST SP 800-101 Rev.1:2014 and ISO/IEC 27037:2012. This study proposes and analyzes an integrated implementation of these two forensic guidelines. The result of this will provide a forensic investigator with a good understanding of the two forensic standards, and present an opportunity to forensic investigators, organizations and jurisdictions that are compliant in one standard to realize the benefits of the other standard. As it is shown, no single standard addresses all processes of digital forensic investigations. This comparison identifies areas of forensics guidelines covered by each standard, commonalities and differences in the two standards, and their limitations.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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