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QIF-T0020

medium

Membership inference on neural data

Tier 4 — Demonstrated (Case Study / Observational)

Legacy status: EMERGING

Determine if a specific person's neural data was used to train a BCI model. Reveals participation in clinical trials, neurological conditions. GDPR Article 9 implications.

Technique Details

Tactic
QIF-M.SV
Status
EMERGING
Bands
S2, S3

Therapeutic Application

Statistical inference to determine if specific neural data was used in BCI model training

Clinical Analog

Clinical trial participation verification

Treats

  • clinical trial auditing
  • research data governance

Neural Impact

2 of 7 neural bands affected

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:L/CD:L/CV:I/RV:F/NP:N
CVSS v4.0 CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N
2.7Low
BICRCDCVRVNP
 

Governance

Neurorights at Risk

This technique threatens 1 of the 4 proposed neurorights (Ienca & Andorno, 2017).

Consent Complexity
0.20 / 4.0

FDORA §3305 Compliance

Cyber Device
Regulatory Coverage
0.4 / 1.0
524B Requirements
TM VA 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) 2.7 2.7 Low -
Child (10yr) + ADHD 2.7 3.2 Low +0.48
Adult with ALS 2.7 3.1 Low +0.44

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