Credible BGP – Extensions to BGP for Secure Networking
Bibliographic record
Abstract
Border Gateway Protocol (BGP) is the de-facto routing protocol in the Internet. Unfortunately, it is not a secure protocol, and as a result, several attacks have been successfully mounted against the Internet infrastructure. Among the security requirements of BGP is the ability to validate the actual source and path of the BGP update message. This is needed to help reduce the threat of prefix hijacking and IP spoofing based attacks. BGP route associates an address prefix with a set of autonomous systems (AS) that identify the inter-domain path that the prefix has traversed in the form of BGP announcements. This set is represented as the AS_PATH attribute in BGP and starts with the AS that originated the prefix. Credible BGP (CBGP) proposes several extensions to BGP protocol to validate source and path of BGP update message and to use the resulting validation score to influence the route selection algorithm. CBGP assigns credibility scores for AS prefix origination and AS_PATH. These credibility scores are used in the extended selection algorithm to prefer valid BGP routes. The new protocol can detect BGP attacks such as AS Path Injection and AS Prefix high jacking.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".