Keychain-Based Signatures for Securing BGP
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
As a major component of Internet routing infrastructure, the Border Gateway Protocol (BGP) is vulnerable to malicious attacks. While Secure BGP (S-BGP) provides a comprehensive framework to secure BGP, its high computational cost and low incremental deployment benefits seriously impede its wide usage in practice. Using a lightweight symmetric signature scheme, SPV is much faster than S-BGP. However, the speed boost comes at the price of prohibitively large signatures. Aggregated path authentication reduces the overhead of securing BGP in terms of both time and space, but the speed improvement is still limited by public key computation. In this paper, we propose a keychain-based signature scheme called KC-x. It has low CPU and memory overheads and provides strong incentive for incremental deployment on the Internet. As a generic framework, KC-x has the flexibility of using different signature algorithms, which can even co-exist in a hybrid deployment. We investigate two implementations of KC-x: KC-RSA based on RSA and KC-MT based on Merkle hash tree. Using real BGP workloads, our experimental results show that KC-RSA is as efficient as SAS-V (the most efficient software approach for aggregated path authentication), and KC-MT is even three times faster than SPV with 40% smaller signatures. Through the hybrid deployment of KC-MT and KC-RSA, KC-x can achieve both small signature and high processing rate for BGP speakers.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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