FPGA implementation of two involutional block ciphers targeted to wireless sensor networks
Bibliographic record
Abstract
In this paper, we investigate the energy cost of the FPGA implementation of two cryptographic algorithms targeted to wireless sensor networks (WSNs). Recent trends have seen the emergence of WSNs using sensor nodes based on reconfigurable hardware, such as a field-programmable gate arrays (FPGAs), thereby providing flexible functionality with higher performance than classical microcontroller based sensor nodes. In our study, we investigate the hardware implementation of involutional block ciphers since the characteristics of involution enables performing encryption and decryption using the same circuit. This characteristic is particularly appropriate for a wireless sensor node which requires the function of both encryption and decryption. Further, in order to consider the suitability of a cipher for application to a wireless sensor node, which is an energy constrained device, it is most critical to consider the cost of encryption in terms of energy consumption. Hence, we choose two involutional block ciphers, KHAZAD and BSPN, and analyze their energy efficiency for FPGA implementation.
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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 | 0.000 | 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) | 0.002 | 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 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".