Scalable Elliptic Curve Cryptosystem FPGA Processor for NIST Prime Curves
Bibliographic record
Abstract
The architecture and the implementation of a high-performance scalable elliptic curve cryptography processor (ECP) are presented. The proposed ECP is able to support all five prime field elliptic curves recommended by the National Institute of Standards and Technology (NIST). The design takes advantage of the high-performance capabilities of the DSP48E slices available in Xilinx field-programmable gate arrays (FPGAs) to achieve high speed and low hardware resource utilization. The proposed design parallelizes the underlying prime field operations to reduce the latency of the elliptic curve point multiplication (ECPM) operation. Prime field inversion is performed efficiently using the same arithmetic blocks as the ones used for prime field multiplication and addition/subtraction. To the best of the authors' knowledge, the proposed scalable ECP is the fastest and smallest ECP that can support all five NIST recommended prime curves without the need to reconfigure the hardware. It can compute the ECPM between 1.709 and 28.04 ms using a Xilinx Virtex-5 FPGA.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".