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
The susceptibility of wireless portable devices to electromagnetic (EM) attacks is largely unknown. If analysis of electromagnetic (EM) waves emanating from the wireless device during a cryptographic computation do leak sufficient information, it may be possible for an attacker to reconstruct the secret key. Possession of the secret cryptographic key would render all future wireless communications insecure and cause further potential problems, such as identity theft. Despite the complexities of a PDA wireless device, such as operating system events, interrupts, cache misses, and other interfering events, this article demonstrates that, for the first time, repeatable EM differential attacks are possible. The proposed differential analysis methodology involves precharacterization of the PDA device (thresholding and pattern recognition), and a new frequency-based differential analysis. Unlike previous research, the new methodology does not require perfect alignment of EM frames and is repeatable in the presence of a complex embedded system (including cache misses, operating system events, etc), thus supporting attacks on real embedded systems. This research is important for future wireless embedded systems, which will increasingly demand higher levels of security.
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 | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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