Specification-based Intrusion Detection for home area networks in smart grids
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
Achievement of the goals of smart grid such as resilience, high power quality, and consumer participation strongly depends on the security of this system. Along with the security measures that should be built into the smart grid from the beginning, appropriate Intrusion Detection Systems (IDSs) should also be designed. Home area network (HAN) is one of the most vulnerable subsystems within the smart grid, mostly because of its physically insecure environment. In this paper, we present a layered specification-based IDS for HAN. Considering that ZigBee is the dominant technology in future HAN, our IDS is designed to target ZigBee technology; specifically we address the physical and medium access control (MAC) layers. In our IDS the normal behavior of the network is defined through selected specifications that we extract from the IEEE 802.15.4 standard. Deviations from the defined normal behavior can be a sign of some malicious activities. We further investigate the physical and MAC layer attacks in ZigBee networks and evaluate the performance of our proposed IDS against them. Our IDS provides a good detection capability against known attacks, and since this is an IDS based on anomalous event detection, we expect the same for unknown attacks.
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 | 0.000 |
| 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