Improved Authentication in Information Systems through a Mobile Identity Management Scheme (MoIdM-MSS) Utilizing Mobile Signature Service
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
In today's digital economy, work processes are increasingly digitized using computer information systems. An essential aspect of employees' reliance on these systems is trust in their reliability. Mobile devices and apps play a vital role in this digital landscape, with Mobile Identity at the forefront. Mobile Identity extends the concept of digital identity through mobile networks, acting as a tool for login and transactions and as a crucial element in communication and interaction. This paper introduces a Mobile Identity Management Scheme based on the Mobile Signature Service for information systems. The scheme enables digital signatures on mobile devices for various purposes, enhancing security by leveraging the user's private key and the system's authentication challenge. Through this approach, authentication is ensured by permitting only users with the correct private key to sign the challenge, eliminating the necessity for traditional authentication methods such as usernames and passwords. Furthermore, the scheme leverages mobile device security features like secure computing environments and biometric authentication to bolster authentication. By adding an extra layer of protection and focusing on user convenience, security is heightened without introducing unnecessary complexity. Evaluations conducted in local signing scenarios have demonstrated the scheme's effectiveness, acceptance, and potential, indicating promising results for its application in enhancing work process security.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.013 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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