Towards a Decentralized Access Control System for IoT Platforms based on Blockchain Technology
Bibliographic record
Abstract
The Internet of Things (IoT) technologies are transforming traditional businesses into digital-based platforms allowing for more service innovation, performance efficiency and customer satisfaction. Novel services enable users to utilize their personal devices (eg. mobile phones or laptops) to access the IoT platform, process data, and control the IoT infrastructure. However, these services impose critical user authentication and access control requirements. In this paper, we propose a decentralized user authentication and access control system for the IoT platforms via a permissioned blockchain network. We define an authorization sensitivity factor to provide clients with specific access control privileges and we consider an ehealth system as a use case example to demonstrate our solution. The proposed system is implemented using Ethereum platform. Besides, we investigate a threat model that considers an insider Distributed Denial of Service (DDoS) attack. The proposed defense mechanism utilizes a modifier function in the smart contract and keeps a real-time record of legitimate users to restrict function calls. The results illustrate the benefits of the defense mechanism in terms of the system response time.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".