A secure scan chain using a phase locking system and a reconfigurable LFSR
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
Scan chains are exploited to develop attacks on cryptographic hardware to extract secret information. For a scan-enabled chip, the probability of success increases if a user has unlimited access to apply test patterns to the Circuit-Under-Test (CUT) and observe the responses. In this paper, two layers of security have been proposed to protect scan architecture against hackers. A tester authentication method utilizing a Phase Locked Loop (PLL) to encrypt the operating frequency of both CUT/Tester is presented. Moreover, the CUT authenticates the tester to grant access to the scan chain. In the test mode, the direct access to the scan flip-flops is not granted to protect their secret information against attackers. A built-in self-test scheme (BIST) using a reconfigurable LFSR is designed to test the scan flip-flops in the test mode.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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