Rogue Device Detection via Redundant Environmental Telemetry from Cargo Aircraft Operations

Overview This dataset contains one-second-resolution time-series telemetry recorded during real cargo aircraft flight operations (Antonov), augmented with two synthetic sensor spoofing scenarios. It is designed as a benchmark resource for unsupervised anomaly detection methods on univariate and multivariate sensor time series. The dataset captures four environmental parameters: altitude (H), atmospheric pressure (Pr), temperature (T), and relative humidity (Hum); each measured simultaneously by two independent sensors (Sensor 1, Sensor 2). The agreement between paired sensors is the core anomaly signal: under healthy operation, the redundant sensors track each other closely; under a fault condition, Sensor 2 diverges from its paired reference (Sensor 1). Sensor Architecture and Anomaly Signal Each parameter is instrumented with a redundant pair: Pair Parameter Unit Sensor 1 (reference) Sensor 2 (monitored) H Barometric altitude m H1 H2 Pr Atmospheric pressure Pa Pr1 Pr2 T Temperature °C T1 T2 um Relative humidity % Hum1 Hum2 Sensor 1 is the trusted reference throughout all scenarios. Anomalies are expressed as inter-sensor divergence: |S1 − S2| exceeds its normal operating bounds when Sensor 2 is under sensor spoofing. This redundancy-based detection principle supports the identification of rogue or malfunctioning sensor devices connected to the monitoring system. Files All files contain 11,425 rows (one row per second) and 9 columns. The files are unlabeled; no per-row anomaly flag column is included in this release. Column Description Unit time Unix timestamp s H1 Barometric altitude, Sensor 1 — reference m H2 Barometric altitude, Sensor 2 — monitored m Pr1 Atmospheric pressure, Sensor 1 — reference Pa Pr2 Atmospheric pressure, Sensor 2 — monitored Pa T1 Temperature, Sensor 1 — reference °C T2 Temperature, Sensor 2 — monitored °C Hum1 Relative humidity, Sensor 1 — reference % Hum2 Relative humidity, Sensor 2 — monitored % Scenarios flight001_normal.csv - Nominal operation (real data). Real flight telemetry with no injected faults. Both sensors in each pair agree throughout the full flight arc. This file represents healthy operation and serves as the training baseline for unsupervised anomaly detection models. flight001_mixed.csv - Intermittent sensor spoofing (synthetic). Sensor 2 channels (T2, Pr2, H2, Hum2) receive periodic burst noise in repeating on/off intervals, while Sensor 1 retains the original recorded signal. During active sensor spoofing ( fault windows), Sensor 2 oscillates across the full physical range of each channel (e.g., Pr2: 0–150,000 Pa; T2: 5–40 °C; Hum2: −20–80 %). Between bursts, Sensor 2 briefly returns to nominal and converges with Sensor 1. The burst pattern is synchronised across all four affected channels. This scenario models intermittent or transiently degrading sensor behaviour. flight001_rogue.csv - Complete sensor spoofing (synthetic). Noise of the same amplitude as the mixed scenario is applied continuously and without interruption throughout the entire flight. No recovery windows occur. Sensor 2 readings are fully corrupted from the first to the last sample; only Sensor 1 retains the true flight signal. This scenario models total, non-recoverable sensor failure. Noise Injection Methodology Noise was injected exclusively on Sensor 2 (T2, Pr2, H2, Hum2); Sensor 1 (T1, Pr1, H1, Hum1) retains the original recorded values in all three files. The injected values (noise) are drawn from a uniform distribution spanning the full physical range of each channel. The resulting noise amplitudes observed in the data are: Channel Normal operating range Noise amplitude under fault T2 20–27 °C 5–40 °C Pr2 51,000–101,000 Pa 0–150,000 Pa H2 0–5,200 m suppressed by the altitude scale Hum2 10–65 % −20–80 % In the mixed scenario, noise is applied in discrete time blocks, giving Sensor 2 a characteristic burst-and-recover pattern. In the rogue scenario, the same noise is sustained for the full duration with no recovery intervals. Supplementary Figures Three figures are included (fig_sensor_pairs_normal_cycle001.png, fig_sensor_pairs_mixed_cycle001.png, fig_sensor_pairs_rogue_cycle001.png), each showing the four redundant sensor pair time series (H1/H2, Pr1/Pr2, T1/T2, Hum1/Hum2) for the corresponding scenario over the full flight cycle. Normal: All four pairs overlap tightly. H1/H2 and Pr1/Pr2 are virtually identical. T1/T2 maintain a consistent natural offset of approximately 1 °C. Hum1/Hum2 co-vary with minor natural spread; humidity falls from ~65 % at ground level to ~12 % at cruise altitude and partially recovers on landing. Mixed: Burst noise is most visible in the Pr1/Pr2 and T1/T2 panels, where Sensor 2 alternates between wide-amplitude oscillations and brief periods of nominal agreement with Sensor 1. The Hum1/Hum2 panel shows the same burst pattern. H1/H2 divergence is less apparent because the noise amplitude is small relative to the 0–5,200 m altitude scale. Rogue: Sensor 2 forms a continuous wide-amplitude noise band in all four panels throughout the entire flight. Sensor 1 is visible only as a thin line within the noise envelope. No convergence occurs at any point.