Hardware Design and Analysis of the ACE and WAGE Ciphers
Bibliographic record
Abstract
This paper presents the hardware design and analysis of ACE and WAGE, two candidate ciphers for the NIST Lightweight Cryptography standardization. Both ciphers use sLiSCP's unified sponge duplex mode. ACE has an internal state of 320 bits, uses three 64 bit Simeck boxes, and implements both authenticated encryption and hashing. WAGE is based on the Welch-Gong stream cipher and provides authenticated encryption. WAGE has 259 bits of state, two 7 bit Welch-Gong permutations, and four lightweight 7 bit S-boxes. ACE and WAGE have the same external interface and follow the same I/O protocol to transition between phases. The paper illustrates how a hardware perspective influenced key aspects of the ACE and WAGE algorithms. The paper reports area, power, and energy results for both serial and parallel (unrolled) implementations using four different ASIC libraries: two 65 nm libraries, a 90 nm library, and a 130 nm library. ACE implementations range from a throughput of 0.5 bits-per-clock cycle (bpc) and an area of 4210 GE (averaged across the four ASIC libraries) up to 4 bpc and 7260 GE. WAGE results range from 0.57 bpc with 2920 GE to 4.57 bpc with 11080 GE.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".