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This dataset provides controlled behavioural execution-response measurements collected from 11 Raspberry Pi devices under a fixed experimental configuration. The dataset is intended to support research on behavioural device profiling, identity establishment, continuous authentication, and robustness analysis using execution-dependent system response signals. Measurements were collected from 3 Raspberry Pi 3 Model B+ devices and 8 Raspberry Pi 4 Model B devices, all operating in a headless, non-graphical environment. Devices were configured to operate at a fixed maximum CPU frequency with CPU core isolation and reduced interrupt interference. Controlled workload routines were executed under pinned scheduling conditions to obtain reproducible measurements of behavioural responses. Data is organised across 4 CPU cores, 5 reboot rounds per device, and 800 samples per reboot. The dataset contains 176,000 total samples. Each sample records temperature measurements, performance counter-derived QPU responses, CPU hash execution responses, pseudo-random generation responses, true-random generation responses, anonymised device identifiers, device model labels, reboot indices, and sample indices. Original hardware identifiers were removed and replaced with stable pseudonymous device identifiers to preserve device consistency while protecting persistent hardware identity information. This dataset is intended for research in behavioural device fingerprinting, identity establishment mechanisms, adversarial robustness evaluation, and privacy-preserving authentication systems.