Energy Efficient Random Forest Classifier-Based Secure Routing for Opportunistic Internet of Things
Why this work is in the frame
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Bibliographic record
Abstract
Opportunistic internet of things (OppIoT) is a class of opportunistic networks, where the data are transmitted in a broadcast manner and shared among the nodes (i.e., IoT devices and human communities' devices) through opportunistic contact. In such networks, taking into consideration the energy level of each node while performing the routing of data is of utmost importance. This paper proposes an energy-efficient secure routing protocol that uses a random forest classifier (called ESRFCSec) for device behaviour predictions and for protecting the OppIoT network against packet collusion attacks. Through simulations, ESRFCSec is shown to achieve a prediction accuracy of 97.97%. It is also shown to be superior to three benchmark routing schemes in terms of node's residual energy, delivery probability, average latency, number of dead nodes, and number of dropped packets.
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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 | 0.000 |
| 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 it