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QIF-T0079

high

Ear canal acoustic fingerprinting (ANC echo profiling for covert identification)

Tier 3 — Demonstrated (Lab-proven)

Legacy status: DEMONSTRATED

Active noise cancellation (ANC) earbuds already contain the complete hardware for ear canal acoustic fingerprinting: an inward-facing (feedback) microphone that measures sound inside the ear canal, an outward-facing (feedforward) microphone, and a speaker that can emit probe tones. When the speaker emits a broadband chirp or swept sine, the inward-facing microphone captures the echo profile shaped by the ear canal's unique geometry: length (~25mm), diameter (~7mm), tympanic membrane compliance, and the specific curvature of the bends. This acoustic transfer function is a biometric — NEC demonstrated it for authentication with >99% accuracy. In the attack scenario, the ANC system's existing probe tones (used for adaptive fit detection and transparency mode calibration) are leveraged to silently fingerprint the wearer without their knowledge. The earbuds know WHO is wearing them at all times. Combined with audioplethysmography (PPG via in-ear speaker/mic measuring blood volume changes), the same hardware simultaneously provides identity + heart rate: a silent surveillance pipeline requiring zero hardware modification on ANC earbuds. Attack surface: firmware update, compromised ANC calibration routine, or malicious SDK in earbud companion app.

Technique Details

Tactic
QIF-S.FP
Status
DEMONSTRATED
Bands
S1, S2, S3

Therapeutic Application

ANC earbud speaker emits probe tone; feedback microphone captures ear canal echo profile shaped by unique anatomical geometry; acoustic transfer function serves as biometric identifier

Clinical Analog

Ear canal acoustic authentication for medical device access control

Treats

  • hearing aid personalization (acoustic fit verification)
  • continuous authentication for hearing-assistive BCIs
  • otoacoustic emission screening (newborn hearing tests)
  • middle ear health monitoring (tympanometry equivalent)

Neural Impact

3 of 7 neural bands affected

S1 S2 S3

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Click or hover over a glowing region to see the attack techniques targeting it and their severity.

Scoring

NISS v1.1 NISS:1.1/BI:N/CR:N/CD:N/CV:I/RV:F/NP:N
CVSS v4.0 CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N
2.0Low
BICRCDCVRVNP
 

Governance

Neurorights at Risk

This technique threatens 2 of the 4 proposed neurorights (Ienca & Andorno, 2017).

Consent Complexity
0.48 / 4.0

FDORA §3305 Compliance

Cyber Device
Regulatory Coverage
0.5 / 1.0
524B Requirements
TM VA SBOM SA PM
Regulatory Gaps
  • ! CVSS partially captures risk; neural dimensions missing
  • ! No FDA pathway for consumer sensor exploitation

Population Vulnerability

CRB vulnerability adjustment (γ=0.30) accounts for age, diagnosis severity, consent capacity, and device dependency.

Population NISS Base Adjusted Severity Delta
Adult (Default) 2.0 2.0 Low -
Child (10yr) + ADHD 2.0 2.4 Low +0.35
Adult with ALS 2.0 2.3 Low +0.32

Validation Status

Theoretical / Not yet validated. This technique has not been independently tested. See the validation dashboard for what has been tested.

Qinnovate Neural Security Atlas Edit this on GitHub