Methodology for attack on a Java-based PDA
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
Although mobile Java code is frequently executed on many wireless devices, the susceptibility to electromagnetic (EM) attacks is largely unknown. If analysis of EM waves emanating from the wireless device during a cryptographic computation does 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 Java-based PDA device, this paper proposes and verifies a methodology which confirms EM attacks are possible. The proposed methodology involves pre-characterization of the PDA device through SEMA, thresholding, pattern recognition, and frequency-based DEMA. Results are repeatable over several different secret keys. Unlike previous research the new methodology does not require perfect alignment of EM frames and demonstrates robustness in the presence of a complex embedded system. 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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