Preventing unauthorized access in information centric networking
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
The increasing traffic volume and new requirements of highly scalable and efficient distribution of contents exceed the capabilities of the current Internet architecture. Information centric networking (ICN) is a new communication paradigm for the next generation internet (NGI), which focuses mainly on contents. ICN has in‐network caching capability, which enables any node to cache any content coming from any publisher. ICN subscribers are able to access contents from different distributed locations. This capability maximizes the problem of unauthorized access to ICN contents. In this paper, we propose a decentralized elliptic curve‐based access control (ECAC) protocol for ICN architectures. In this protocol, fewer public messages are needed for access control enforcement between ICN subscribers and ICN nodes than the existing access control protocols. ECAC protocol depends on ICN self‐certifying naming scheme. We perform security analysis on ECAC for the following attacks: man‐in‐the‐middle, forward security, replay attacks, integrity, and privacy violations. We also evaluate communication, computational, and storage overhead for performance analysis to ECAC. Based on our results that are obtained under various scenarios, ECAC efficiently prevents unauthorized access to ICN contents.
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 | 0.002 |
| Open science | 0.000 | 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