IPSec-based secure wireless virtual private network
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
There is currently enormous interest in the design of secure wireless networks. This has been necessitated by the fact that free-space radio transmission in wireless networks makes eavesdropping easy and consequently, a security breach may result in unauthorized access, information theft, interference, jamming and service degradation. Virtual private networks (VPN) have emerged as an important solution to security threats surrounding the use of public networks for private communications. VPN provide security by integrating a set of authentication, encryption, access control and session management components. While VPN for wireline networks have matured in both research and commercial environments, the design and deployment of wireless VPN is still an evolving field. This paper presents the results of an ongoing sub-project within the Secure Active VPN Environment (SAVE) project at Dalhousie University. The primary objective of this paper is to present the design and implementation of a secure wireless LAN based on the IPSec VPN tunnelling protocol and investigate its performance. An IPSec-compliant VPN is constructed and the traffic between the wireless node and the gateway is protected by the IPSec tunnel. PGP certification is used to provide secure public key management. UDP and TCP performance analysis are done to determine the effects of IPSec service on the wireless VPN. A further TCP trace analysis is done to determine the pipe capacity usage on the wireless VPN.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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