Receiver access control and secured handoff in mobile multicast using IGMP-AC
Bibliographic record
Abstract
Multicasting has not been widely adopted until now, due to lack of receiver or end user (EU) access control. We have developed the Internet group management protocol with access control (IGMP-AC), an extended version of IGMPv3, which provides EU access control by incorporating the AAA framework into the existing multicast service model. Furthermore, IGMP-AC works as an extensible authentication protocol (EAP) lower layer, and thus, supports a variety of different authentication methods. IP multicast will face new challenges if it has to control mobile EUs accessing valuable data in wireless networks. In the absence of receiver access control the operators of the wireless networks will be reluctant to deploy IP multicast, due to possible wastage of valuable bandwidth and other resources from joining of any unauthorized mobile EU and unwanted extension of the distribution tree. Moreover, multicast suffers from denial of service attack more severely than any other attack because of its amplification of data packets enroute. In this paper, we have broadened the scope of IGMP-AC by demonstrating the usability of IGMP-AC in wireless networks for mobile receiver (or EU) access control. In addition, using EAP re-authentication protocol (ERP), we have developed a procedure for secured and fast handoff of mobile EUs in wireless networks.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".