FPGA implementation of two involutional block ciphers targeted to wireless sensor networks
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
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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