Smart grid authentication and key management for unicast and multicast communications
Bibliographic record
Abstract
One of the most important and challenging area in the smart grid context is security and privacy section. Smart grid is a vulnerable system and can be attacked even from aboard, attacks that may cause different level of issues and harms on the devices and society. So, research community has paid attention to this topic and the reasons of required security and privacy for the smart grid. The first step of designing and implementing security for any system such as a smart grid is an authentication scheme followed by a key management protocol. Other security aspects like integrity, authorization and confidentiality can be implemented as long as a strong key management protocol has already been designed and addressed. In this paper we provide a new scheme for the mutual authentication between the smart grid utility network and Home Area Network smart meters. Our proposed mechanism is capable of preventing different attacks like Brute-force, Replay, Man-In- The-Middle and Denial-of-Service attacks. Also, we provide a novel key management protocol for data communication between the utility server and customers smart meters. Our proposed protocol improves the network overhead caused by security key management controlling packets, and at the same time it is enough secured in order to prevent above mentioned attacks. In fact, by generating and broadcasting only one function periodically by the server that is in charge of the network security, our protocol simply refreshes entire nodes public key and private key as well as multicast required security keys if any.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".