A Key Management Scheme for Cluster Based 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
Key management is a major challenge to achieve security in wireless sensor networks. In most of the schemes presented for key management in wireless sensor networks, it is assumed that the sensor nodes have the same capability. The recent research has shown that the survivability of the network can be improved if sensor nodes are grouped in clusters in which a powerful cluster head assigned. However, to gain advantages of clustering in order to find an efficient key management scheme needs more research. In this paper, we investigate the key management in cluster-based wireless sensor networks using both private and public key cryptography. Our goal is to introduce a platform in which public key cryptography is used to establish a secure link between sensor nodes and gateways. Instead of pre-loading a large number of keys into the sensor nodes, each node requests a session key from the gateway to establish a secure link with its neighbors after clustering phase. The security analysis and performance evaluation show that the proposed scheme has significant saving in storage space, transmission overhead, and perfect resilience against node capture.
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