A split-mask countermeasure for low-energy secure embedded systems
Bibliographic record
Abstract
Future wireless embedded devices will be increasingly powerful, supporting many more applications, including one of the most crucial---security. Although many embedded devices offer more resistance to bus---probing attacks because of their compact size, susceptibility to power or electromagnetic analysis attacks must be analyzed. This paper presents a new split-mask countermeasure to thwart low-order differential power analysis (DPA) and differential EM analysis (DEMA). For the first time, real-power and EM measurements are used to analyze the difficulty of launching new third-order DPA and DEMA attacks on a popular low-energy 32-bit embedded ARM processor. Results show that the new split-mask countermeasure provides increased security without large overheads of energy dissipation, compared to previous research. With the emergence of security applications in PDAs, cell phones, and other embedded devices, low-energy countermeasures for resistance to low-order DPA/DEMA is crucial for supporting future enabled wireless internet.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".