Design space exploration of the lightweight stream cipher WG-8 for FPGAs and ASICs
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
WG-8 is a lightweight instance of the Welch-Gong (WG) stream cipher family, targeting for resource-constrained devices like RFID tags, smart cards, and wireless sensor nodes. Recent work has demonstrated the advantages of tower field constructions for finite field arithmetic in the AES and WG-16 ciphers. In this paper we explore three different tower field constructions for WG-8. The first tower field is tailored to FPGA cells. The second tower field uses a Type-I optimal normal basis. The third tower field exploits algebraic properties of the WG permutation and trace functions. All of the methods use a parallel LFSR to provide data rates from one to eleven bits per clock cycle. Among the three tower fields, the Type-I ONB construction offers the best trade-off in area, speed, and power consumption. However, a plain monolithic look-up table implementation with 256 entries is smaller and faster than the tower field constructions. Our analysis of the tower field options and comparisons to each other and to the monolithic look-up table will provide lessons for future work in exploring novel tower field constructions for WG and other ciphers.
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 | 0.001 |
| 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