Secure machine‐type communications in LTE 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
Abstract With a great variety of potential applications, machine‐type communications (MTC) is gaining a tremendous interest from mobile network operators and research groups. MTC is standardized by the 3rd Generation Partnership Project (3GPP), which has been regarded as the promising solution facilitating machine‐to‐machine communications. In the latest standard, 3GPP proposes a novel architecture for MTC, in which the MTC server is located outside the operator domain. However, the connection between the 3GPP core network and MTC server in this scenario is insecure; consequently, there are distrustful relationships among MTC device, core network, and MTC server. If the security issue is not well addressed, all applications involved in MTC cannot be put into the market. To address this problem, we propose an end‐to‐end security scheme for MTC based on the proxy‐signature technique, called E 2 S E C . Specifically, both the MTC device and MTC server can establish strong trustful relationships with each other by using the proxy signatures issued by the 3GPP core network. Moreover, we present some implementation considerations of E 2 S E C and analyze the performance during authentication by comparing the operational cost of three cases that apply three different signature algorithms, that is, ElGamal, Schnorr, and DSA. Through security analysis by using Automatic Cryptographic Protocol Verifier (ProVerif), we conclude that the proposed E 2 S E C scheme can achieve the security goals and prevent various security threats. Copyright © 2015 John Wiley & Sons, Ltd.
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 | 0.000 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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