QIF-T0097
criticalCross-device physiological correlation (phone + watch + earbuds comprehensive health profiling)
Tier 5 — Theoretical (Modeled / Simulated)
Legacy status: THEORETICAL
The average consumer now carries 3+ sensor-equipped devices: smartphone (accelerometer, gyroscope, magnetometer, barometer, camera, microphone, ambient light, proximity, WiFi, BLE), smartwatch (PPG, accelerometer, gyroscope, SpO2, skin temperature, ECG), and earbuds (microphone, accelerometer, proximity, potentially EEG). By correlating physiological data across all devices simultaneously, an attacker builds a comprehensive health profile far exceeding what any single device captures: cardiac health (watch PPG + phone rPPG), respiratory health (phone ultrasonic + WiFi CSI), neurological health (earbud IMU tremor + phone motor patterns), mental health (watch HRV + earbud audio context + phone screen activity), and metabolic health (activity + sleep + heart rate patterns). The correlation also eliminates single-sensor noise and improves accuracy. This technique doesn't require hardware modification — only software-level data aggregation across apps on a shared platform (e.g., iOS HealthKit, Google Health Connect).
Technique Details
- Tactic
- QIF-S.CH
- Status
- THEORETICAL
- Bands
- S1, S2, S3, N7
✚ Therapeutic Application
Cross-device physiological data correlation across phone + watch + earbuds to build comprehensive health profile exceeding single-device capability
Clinical Analog
Multi-device remote patient monitoring for chronic disease management
Treats
- heart failure decompensation prediction (multi-sensor)
- diabetes management (activity + sleep + heart rate correlation)
- mental health monitoring (multi-modal behavioral markers)
- clinical trial endpoint monitoring
Neural Impact
4 of 7 neural bands affected
Drag to rotate. Click a region to learn more.
Click or hover over a glowing region to see the attack techniques targeting it and their severity.
DSM-5-TR Diagnostic Mappings
Diagnostic category references for threat modeling, not diagnostic claims.
Pathway: N7 (PFC/M1) → executive function
Following Poldrack (2006), brain region disruption does not uniquely predict psychiatric outcomes.
Scoring
NISS:1.1/BI:N/CR:L/CD:L/CV:I/RV:F/NP:N 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 Governance
Neurorights at Risk
This technique threatens 5 of the 4 proposed neurorights (Ienca & Andorno, 2017).
FDORA §3305 Compliance
- ! CVSS cannot express neural-specific impacts
- ! No FDA pathway for consumer sensor exploitation
- ! 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) | 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.