Comparison of two security protocols for preventing packet dropping and message tampering attacks on AODV-based mobile ad Hoc networks
Bibliographic record
Abstract
In Emergency MANETs (eMANETs), the broadcasting nature of the wireless medium, the lack of pre-established trust relationship among nodes, and the frequent topology changes, cause some serious security challenges, making the network vulnerable to malicious attacks such as wormhole attacks. This paper investigates a recently proposed Advanced Encryption Standard (AES)-based routing algorithm (so-called AODV-Wormhole Attack Detection Reaction - here referred to as AODV-WADR-AES) for securing AODV-based eMANETs against wormhole attacks. The proposal consists of substituting the AES part of the scheme by the Triple Data Encryption Standard (TDES), yielding the AODV-WADR-TDES routing algorithm, with the goal to study the performance of the algorithm where mobile devices that are incompatible with AES are part of eMANET nodes. In doing so, markers in the form of hash codes are included in the data packets to help consolidating the data integrity. Simulation results are presented to validate the proposed AODV-WADR-TDEA scheme. It is also shown that the AODV-WADR-AES scheme outperforms the AODV-WADR-TDES scheme in terms of end-to-end delay, packet delivery ratio, and number of packets traversing through the wormhole link.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".