SARFUM
Bibliographic record
Abstract
Remote update of hardware platforms or embedded systems is a convenient service enabled by Field Programmable Gate Array (FPGA)-based systems. This service is often essential in applications like space-based FPGA systems or set-top boxes. However, having the source of the update be remote from the FPGA system opens the door to a set of attacks that may challenge the confidentiality and integrity of the FPGA configuration, the bitstream. Existing schemes propose to encrypt and authenticate the bitstream to thwart these attacks. However, we show that they do not prevent the replay of old bitstream versions, and thus give adversaries an opportunity for downgrading the system. In this article, we propose a new architecture called sarfum that, in addition to ensuring bitstream confidentiality and integrity, precludes the replay of old bitstreams. sarfum also includes a protocol for the system designer to remotely monitor the running configuration of the FPGA. Following our presentation and analysis of the security protocols, we propose an example of implementation with the CCM (Counter with CBC-MAC) authenticated encryption standard. We also evaluate the impact of our architecture on the configuration time for different FPGA devices.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.166 | 0.076 |
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".