Randomly directed exploration: An efficient node clone detection protocol in wireless sensor 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
Node clone attack, that is, the attempt by an adversary to add one or more nodes to the network by cloning captured nodes, imposes a severe threat to wireless sensor networks. Several distributed detection protocols have been proposed against this attack. However, all of them rely on too strong assumptions and cannot be efficiently applied to most of sensor networks. In this paper, we propose an innovative randomly directed exploration protocol to detect the node clone. Each node need only know its neighbors' information, and then collaborates to forward claiming messages, trying to find out clone. No any specific routing protocols or infrastructures are demanded in the proposed protocol. Therefore, it is highly practical in the general sensor network applications. In addition, the memory requirement of the protocol is almost optimal. Furthermore, the protocol consumes relatively low communication overload, which is not inferior to any previous schemes. The simulation results show that the protocol can achieve high detection probability. Overall, the proposed protocol outweighs previous approaches in terms of practicability and performance.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it