SCARS: Simplified cryptographic algorithm for RFID systems
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
Radio Frequency Identification (RFID) is a technology made popular by the ability of RFID tags to uniquely represent objects. However, they are severely resource-constrained due to design restrictions. This limits their ability to perform complex computations for security. In RFID systems, the priority is to ensure the integrity of messages and entity authentication. We consider message integrity in our work. To ensure message integrity (i.e., the sent message must be the same as the received message), the actual message is usually hashed and transmitted to the receiver along with the encrypted message. However, it is a challenge for resource-constrained devices such as RFID systems to encrypt a message using different algorithms (such as encryption and hashing algorithm). In this paper, we propose a new symmetric key encryption approach that includes integrity as part of the encryption process for RFID systems. With this approach, we do not need to employ hash functions to achieve message integrity, thus leading to computational efficiency.
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 | 0.000 | 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