Interactive two-channel message authentication based on interactive-collision Resistant hash functions.
Bibliographic record
Abstract
Abstract. We propose an interactive message authentication protocol (IMAP) using two channels: an insecure broadband channel and an authenticated narrow-band channel. We consider the problem in the context of ad hoc networks, where it is assumed that there is neither a secret key shared among the two parties, nor a public-key infrastructure in place. The security of our IMAP is based on the existence of Interactive-Collision Resistant (ICR) hash functions, a new notion of hash function security. Our IMAP is based on the computational assumption that ICR hash functions exist. It performs better than message authentication protocols that are based on computational assumptions. That is, while achieving the same level of security, the amount of information sent over the authenticated channel in our IMAP is smaller than the most secure IMAP and Non-interactive Message Authentication Protocol (NIMAP) in the literature. In other words, if we send the same amount of information over the authenticated channel, we can allow much stronger adversaries compared to the existing protocols in the literature. Moreover, our IMAP benefits from a simple structure and works under fewer security assumptions compared to other IMAPs in the literature. The efficient and easy-to-use structure of our IMAP makes it very practical in real world ad hoc network scenarios.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".