Security mechanism for voice over multipath mobile<i>ad hoc</i>networks
Bibliographic record
Abstract
Abstract In the next generation of wireless communication systems, there will be a need for the rapid deployment of independent mobile users for video and voice communication over wireless network. It can be seen that since the demand for Voice over IP (VoIP) over wireless network is growing, the use of VoIP over mobilead hocnetwork (MANET) is expected to grow as well. However, security is a critical issue in MANETs where mobile nodes communicate with each other over relatively unreliable wireless links without any preexisting infrastructure. In this paper, we present a framework for secure voice transmission over multipath MANET. An efficient traffic allocation approach for multipath MANET is proposed in order to deliver real‐time traffic over it. The proposed security mechanism was evaluated through two analyses. The correctness of the proposed mechanism was proved using Gong, Needham, and Yahalom (GNY) logic while the security analysis shows that the proposed scheme is resistant to various attacks. For the performance evaluation of the proposed framework, simulations were conducted and the results of the simulation experiments show that it is efficient and robust in terms of various performance metrics. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".