Mixed-Signal Physically Unclonable Function With CMOS Capacitive Cells
Bibliographic record
Abstract
An electronic physically unclonable function usually includes an on-chip error-correcting code unit, which is vulnerable to security attacks and adds area, power, and data processing time overheads. This paper proposes a mixed-signal physically unclonable function circuit for authentication purposes, which we call the enhanced capacitive physically unclonable function. It divides the input challenge word over multiple computational groups to decrease processing time, increase security, and eliminate the need for error-correcting code units. Most of the challenge bits control capacitive networks grouped into several capacitive cells, while some are analogized through two digital-to-analog converters. One digital-to-analog converter controls the discharge loads of the capacitive cells; the other controls the reference voltage of comparator units. Each comparator controls a counter that digitizes the discharge time into a response chunk. Most of these counters operate at high frequencies for more precise time-to-digital conversion and are overflown to act as roulettes to promote unpredictability. One counter is not overflown to generate a reference response chunk to support error handling. The design allows for more intrinsic variations throughout the fabrication process, leading to unique response chunks. It applies an expanding challenge-response pair approach, generating a 128-bit response word for a 64-bit challenge word. The capacitive nature of the design supports various security features. Simulating the circuit using 45 nm complementary metal-oxide semiconductor technology resulted in an average power of 921.67 μW, a layout area of 22,470 μm2, and an average data processing time of 118 μs.
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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 | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".