A New 16-Bit IoT ASIC Design for the AES Encryption Algorithm
Why this work is in the frame
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Bibliographic record
Abstract
Previous works to secure IoT devices have mainly focused on 8-bit hardware architectures for AES encryption. In this paper, we present a new 16-bit ASIC design for AES encryption optimized for IoT systems. Our design includes a new 16-bit key derivation circuit that generates keys dynamically in parallel with the datapath, enhancing security by avoiding key exposure and protecting against existing attacks. Our design employs column-wise byte ordering for both the datapath and key derivation, eliminating the need for external reordering and reducing hardware resource usage. Additionally, we design a lightweight 16-bit serial MixColumns circuit that supports higher data rates compared to existing designs. ASIC implementation results using a 65nm CMOS technology library demonstrate a 50% increase in throughput with a 21% increase in area over previous 8-bit based designs. Our lightweight and fast AES ASIC design offers a tailored solution for securing IoT systems.
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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 | 0.001 | 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) | 0.000 | 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