Hardware implementation of a high speed self-synchronizing cipher mode
Bibliographic record
Abstract
Pipelined statistical cipher feedback (PSCFB) mode is a new mode of operation for block cipher encryption. It is an improved version of conventional SCFB mode with higher throughput. SCFB mode has the mechanism of self synchronization to recover from bit slips during transmission in a communication channel. The mechanism of SCFB mode resembles output feedback (OFB) mode and cipher feedback (CFB) mode. However it has self synchronization that OFB mode does not and has higher efficiency than CFB mode. To improve the throughput, PSCFB is a modified version of SCFB that allows for the pipelining of the underlying block cipher while still preserving the efficiency and self-synchronizing capabilities. In this paper, the Advanced Encryption Standard (AES) with a pipeline architecture is used as the block cipher in PSCFB. The PSCFB system is designed, simulated and synthesized targeted to an Altera Cyclone IV FPGA. The structures and processes of both the encryption and decryption are presented. The system performance is analyzed based on the simulation and synthesis results.
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.
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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".