A Structure-independent Approach for Fault Detection Hardware Implementations of the Advanced Encryption Standard
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
The Advanced Encryption Standard, which is used extensively for secure communications, has been accepted recently as a symmetric cryptography standard. However, occurrence of the internal faults by intrusion of the attackers may cause confidential information leak to reveal the secret key. For this reason, several schemes for fault detection of the transformations and rounds in the encryption and decryption of the Advanced Encryption Standard are proposed. In this paper, we present a structure-independent fault detection scheme for the Advanced Encryption Standard. The proposed scheme is independent of the way S- box (inverse S-box) is constructed and can be used for both encryption and decryption. It can be applied to both the S-boxes (and inverse S-boxes) using look-up tables as well as those utilizing logic gate implementations based on composite fields. We have obtained the formulations for the fault detection of the SubBytes (inverse SubBytes) using the relation between the input and output of the S-box (inverse S-box). Then, we have proposed and simulated a signature-based structure-independent fault detection scheme. Moreover, the FPGA implementations of the original and the proposed schemes as well as their overhead are presented.
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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 | 0.000 | 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 | 0.000 | 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