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QIF-T0105

high

Neural sybil

Tier 5 — Theoretical (Modeled / Simulated)

Legacy status: THEORETICAL

Create multiple fake neural node identities to overwhelm consensus or trust mechanisms in multi-electrode/multi-node BCI networks. Analogous to Sybil attacks in distributed systems. From Murcia neural cyberattack taxonomy.

Technique Details

Tactic
QIF-N.IJ
Status
THEORETICAL
Bands
I0, N1

Therapeutic Application

Creating multiple fake BCI node identities to subvert reputation or consensus mechanisms in distributed neural networks

Neural Impact

2 of 7 neural bands affected

I0 N1

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Scoring

NISS v1.1 NISS:1.1/BI:L/CR:H/CD:H/CV:E/RV:P/NP:N
4.7Medium
BICRCDCVRVNP
 

Governance

Neurorights at Risk

This technique threatens 3 of the 4 proposed neurorights (Ienca & Andorno, 2017).

Consent Complexity
0.36 / 4.0

FDORA §3305 Compliance

Non-Cyber Device (missing: software)
Regulatory Coverage
0.1 / 1.0
524B Requirements
TM VA SA PM
Regulatory Gaps
  • ! CVSS cannot express neural-specific impacts
  • ! Threat not yet in regulatory threat catalogs

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) 4.7 4.7 Medium -
Child (10yr) + ADHD 4.7 5.5 Medium +0.83
Adult with ALS 4.7 5.5 Medium +0.76

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