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
Chained HotStuff is a state-of-the-art Byzantine fault-tolerant protocol for building decentralized systems like blockchains. Although chained HotStuff has been widely adopted in many systems, its performance (e.g., throughput and latency) under attacks is still under-explored. In this paper, we develop a multi-metric evaluation framework to quantitatively analyze the performance of chained HotStuff with respect to its chain growth rate, chain quality, and latency. We propose several new attack strategies and evaluate their effects on the performance of chained HotStuff. Our analysis shows that the chain growth rate (resp, chain quality) of chained HotStuff under our attacks can drop to <inline-formula><tex-math notation="LaTeX">$4/9$</tex-math></inline-formula> (resp, <inline-formula><tex-math notation="LaTeX">$12/17$</tex-math></inline-formula>) of that without attacks when one-third of nodes are Byzantine. In addition, we use our framework to evaluate a variant of chained HotStuff, DiemBFT and find that some engineering optimizations render it more vulnerable to some attacks than the original chained HotStuff. Finally, we provide two countermeasures, i.e., broadcasting QCs and the longest chain rule, to thwart these attacks. Our analysis shows that the proposed countermeasures can significantly reduce the latency (almost half of that in chained HotStuff) and make it impossible for an attacker to lower the chain quality by simple attacks.
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 | 0.001 |
| Science and technology studies | 0.001 | 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