Toward a Secure Zero-Touch Tactile Internet: Challenges and Opportunities
Bibliographic record
Abstract
Tactile Internet (TI) is a new generation of communication networks, extending beyond 5G/6G capabilities to achieve ultra-low latency, ultra-responsive, ultra-high availability, and ultra-high reliability communication services and thus enabling a new era of real-time applications, such as virtual reality, remote surgery, and autonomous driving. TI is expected to revolutionize many industries, including healthcare, transportation, and manufacturing. Despite recent TI initiatives, security aspects remain largely unexplored. TI presents several security challenges due to the increased complexity of the network and the criticality of the applications it supports. Thus, security aspects must be carefully designed to ensure that the benefits of the TI are not outweighed by the risks. In this article, we will initially identify the leading factors that drive TI, with regard to their applications and related technological trends, with respect to ETSI's Zero-touch Service Management (ZSM) principles. Then, we shed light on the primary security challenges, the current missing building blocks toward secure TI, and propose some potential solutions. Finally, we conclude the article with several recommendations and observations for the roadmap toward secure TI. Ultimately, the focus of this article is to establish a foundation for more in-depth research on TI security.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".