Security risk assessment in IoT environments: A taxonomy and survey
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
Internet of Things (IoT) applications have become an integral part of our daily lives. However, due to the rising number of cybercrimes, ensuring cyberspace security has become essential. The security and privacy of IoT applications are fundamental as they are used in critical sectors, like healthcare, transportation systems, and energy production. As a result, many studies are focusing on the security and privacy of the IoT revolution. The need for assessing IoT security risks is increasing. This paper presents a survey and taxonomy of risk management, analysis, and evaluation methods applied to systems involving IoT devices. In particular, the paper reviews and categorizes existing IoT risk management and assessment frameworks, and the different assessments techniques, risk perspectives, and methodologies. The paper concludes with a deep analysis of these frameworks, solutions, and guidelines, and discusses future research directions.
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 | 0.002 | 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 | 0.001 | 0.002 |
| 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 it