NIS01-5: A Novel Voting Mechanism for Compromised Node Revocation in Wireless Ad Hoc Networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Due to the nature of wireless ad hoc networks such as dynamic infrastructure and non-centralized management, the routing process has a huge exposure to malicious hacking and intrusions. This fact results in a likelihood of node compromise, leading to a disruption of the legitimate network functions/services. Most reported studies in coping with the problem have focused on the effort of protection on route discovery and data transmission against various attacks. In this paper, we solve the problem from a different perspective by targeting the node compromise revocation, i.e., isolating and breaking off the misbehaving nodes. To mitigate the security breaches from internal compromised nodes and eventually eliminate compromised nodes from the wireless ad hoc networks, we propose an energy efficient malicious node removal mechanism. Further, a new attack on routing service called entrap attack is introduced, where an innocent node is incriminated as a malicious node.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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