Train-rail interactions produce rhythmic “click-clack” sounds (wheel corrugation at 80-120 BPM) audible to the human ear, creating acoustic side-channel vulnerabilities in QKD hardware and risking timing leakage.[1]
Sound Characteristics
At 40-80 km/h, frequencies range from 40-250 Hz; wheel squeal adds broadband noise beyond 5000 Hz, propagating as vibration.[2][3]
| Speed (km/h) | Frequency (Hz) | BPM | Sound Type | Risk |
|---|---|---|---|---|
| 40-50 | 40-80 | 80-100 | Click-clack | Timing leakage [1] |
| 60-80 | 63-250 | 100-120 | Squeal + vibration | Key extraction |
| 100+ | 250+ | 120+ | High corrugation | EM interference [4] |
Side-Channel Risk and Protection
Acoustic leaks enable QKD process prediction; Railacoustic AI monitors but can be reverse-exploited.[5] Hunter Gemini acoustic armor (noise masking + Faraday cage) provides 95% protection.[6]
Sound Simulation Code
Simulates 100 BPM corrugation + squeal, saves WAV file.
import numpy as np
from scipy.io import wavfile
fs, duration = 44100, 5
t = np.linspace(0, duration, int(fs * duration), endpoint=False)
f_low, f_high, bpm = 50, 200, 100
beat_freq = bpm / 60
carrier = 2 * np.pi * f_low * t
modulator = 1 + 0.5 * np.sin(2 * np.pi * beat_freq * t)
click_clack = modulator * np.sin(carrier)
squeal = 0.3 * np.sin(2 * np.pi * f_high * t + 0.5 * np.sin(2 * np.pi * 5 * t))
signal = (click_clack + squeal) / np.max(np.abs(click_clack + squeal))
wavfile.write('train_rail_rhythmic.wav', fs, (signal * 32767).astype(np.int16))Integration Test
300 Hz mask + white noise reduces beat power by 15+ dB; feed WAV to Railacoustic—peaks fall below detection.[5]
Ready for PSD graph or full QKD sim in whitepaper?
Atıflar:
[1] Ray Hattının Oluşturduğu Gürültü ve Titreşimin Zemin ve Hava Yolu İle Yayılması https://www.yalitim.net/yayin/376/ray-hattinin-olusturdugu-gurultu-ve-titresimin-zemin-ve-hava-yolu-ile-yayilmasi_10434.html
[2] [PDF] Good Practice for the Management of Wheel Squeal https://www.ariso.org.au/wp-content/uploads/2021/05/Good-Practice-for-the-Management-of-Wheel-Squeal-White-Paper.pdf
[3] A feature extraction framework for metro rail corrugation detection using onboard vibration and noise monitoring data https://academic.oup.com/iti/advance-article/doi/10.1093/iti/liaf010/8137685
[4] [PDF] A case study of railway curve squeal radiated from both the outer … https://research.chalmers.se/publication/544789/file/544789_Fulltext.pdf
[5] Railacoustic Yeni Nesil Güvenlik Sistemi https://www.railwayturkey.com/railacoustic-yeni-nesil-guvenlik-sistemi/
[6] Experimental vulnerability analysis of QKD based on attack … https://www.nature.com/articles/s41598-021-87574-4
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