Current drainage induced by bias injection attack against Kalman filter of BLDC motor
Bibliographic record
Abstract
False data injection attack against Kalman filter based observer of the linear system in the closed loop control is considered under condition of periodic modulation of the injected data dynamics. Aimed is synergistic effect due to synchronization of the false data dynamics with that of the linear system and interaction with the controller. For that, operation of closed loop controlled Brushless DC (BLDC) motor with Kalman filter in the feedback loop is simulated in Matlab environment under condition of adversarial bias injection attack. Implemented is model of position sensorless drive in which Kalman filter estimates the rotor’s position and angular speed based on phase relations between currents in the motor windings. Adversarial bias injection is implemented into the feedback line of angular velocity estimates connecting output of the Kalman filter and the comparator node, so that Kalman filter estimates are substituted by the ones with the bias included. Here the effect of various bias functions is tested on the control system operation. Specifically, considered are (i) double step-function bias, (ii) gradual linear increase of the bias (triangle function), (iii) saw tooth function with triangular tooth shape, all acting as modification term for Kalman filter estimates of rotor’s speed. Findings for P-type controlled circuits show standard response to the step-function, as expected. Unusually, the gradual linear increase of the injected bias leads to reactive response of the circuits at the initial phase, which counters the bias shift in a way contrary to the step-function response type. This countering weakens as the linear increase of the bias persists, finally turning to the trend aligned with the bias direction. Even more unusually, saw tooth function of the bias causes resonance type of circuit’s response with persistent countering of the bias trend and significant current increase in the motor’s windings, defined here as “current drainage”. Signatures of specific responses are shown to depend on frequency and modulation depth of the bias tooth saw function. Importantly, high levels of current drainage are shown to be achievable at the very low levels (ca. 2%) of bias modulation amplitude for a saw tooth bias functions. This feature holds a promise of potentially devastating tool for stealthy adversarial attacks with high efficiency.
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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 | 0.000 |
| 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 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".