Anonymous authentication and secure communication protocol for wireless mobile <i>ad hoc</i> networks
Bibliographic record
Abstract
Abstract The main characteristic of a mobile ad hoc network (MANET) is its infrastructure‐less, highly dynamic topology, which is subject to malicious traffic analysis. Malicious intermediate nodes in MANETs are a threat concerning security as well as anonymity of exchanged information. In this paper, we propose an anonymous on‐demand routing protocol, called RINOMO, to protect anonymity and achieve security of nodes in MANETs. After successful authentication of the legitimate nodes in the network they can use their pseudo IDs for secure communication. Pseudo IDs of the nodes are generated considering pairing‐based cryptography. Nodes can generate their pseudo IDs independently and dynamically without consulting with system administrator. As a result, RINOMO reduces pseudo IDs maintenance costs. Only trust‐worthy nodes are allowed to take part in routing to discover a route. To ensure trustiness each node has to make authentication to its neighbors through the designed anonymous authentication process. Thus, RINOMO safely communicates between nodes without disclosing node identities. It also provides different desirable anonymous properties such as identity privacy, location privacy, route anonymity, and robustness against several attacks. Mathematical analysis of privacy loss is also evaluated and it shows there is no loss of privacy with respect to time. Thus, RINOMO is an anonymous robust protocol in MANETs. Copyright © 2008 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".