A low-cost S-box for the Advanced Encryption Standard using normal basis
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 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.
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