# CareNet: Linking Home-router Network Traffic to DSM-5 Depressive Behavior Indicators

arXiv: https://arxiv.org/abs/2511.12772 · HTML: https://mlsanity.com/paper/2511.12772/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Nov 2025.

## Built on by (most cited first, 1 of 1)

- [From Packets to Patterns: Interpreting Encrypted Network Traffic as Longitudinal Behavioral Signals](https://mlsanity.com/paper/2605.01616/) (2026)

## Abstract (arXiv)

Digital mental-health sensing increasingly depends on mobile or wearable devices that require intrusive permissions and continuous user compliance. We present CareNet, a router-centric system that transforms household network metadata into interpretable behavioral indicators aligned with DSM-5 depressive-symptom domains. All processing occurs locally at the home gateway, preserving privacy while maintaining visibility of temporal routines. The core contribution is the Fuzzy Additive Symptom Likelihood (FASL), a transparent formulation that fuses header-level metrics into daily criterion-level likelihoods using bounded fuzzy memberships and additive aggregation. Combined with a DSM-style temporal gate, FASL integrates short-term traffic fluctuations into persistent, clinically interpretable indicators. Evaluation on realistic multi-day traces shows that CareNet captures characteristic patterns such as delayed sleep timing and attentional instability without payload inspection. The results highlight the feasibility of reproducible, explainable behavioral inference from router-side telemetry.