A low-cost S-box for the Advanced Encryption Standard using normal basis
Bibliographic record
Abstract
The advanced encryption standard (AES) is a newly accepted secret key cryptographic standard for secure transfer of blocks of data. Among different transformations, the SubBytes transformation is the most expensive one in terms of the chip area and the power consumption in the hardware implementation of the AES. It consists of 16 S-boxes and hence the hardware optimization of the S-box is critical to reach a low-cost AES. In this paper, we present a low-cost S-box for the AES. Instead of using look-up tables for implementing the S-box, logic gate implementation based on a previously known low-complexity composite field using normal basis is utilized. Then, we present improved formulations for the inversion in the sub-fields within the S-box to reduce the area complexity of the implementations. After analyzing the complexities of the new architecture, we compare the ASIC implementation of the proposed S-box using 0:18mu CMOS technology with the previous ones. It is shown that the presented scheme has the lowest power consumption and area compared to its counterparts available in the open literature.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".