{
  "id": 14439,
  "url": "https://arxiv.org/abs/2607.25968v1",
  "title": "E-MagDiP: Electro-Magnetic based Differential Privacy for EEG based Community Sensing",
  "summary": "EEG-based community sensing programs are emerging globally as a tool to leverage aggregated brain data to gain insights into attentiveness of students and employees. But these programs raise privacy concerns because EEG signals contain sensitive personal information. Differential Privacy (DP) can protect individuals while preserving aggregate statistics yet applying DP to EEG data is challenging as it requires user-level noise generation, which increases power and latency. Besides, most commerci",
  "authors": "Ayanga Imesha Kumari Kalupahana, Vishruti Ranjan, Li-Shiuan Peh",
  "category": "research",
  "topics": "privacy-surveillance,children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-28T16:50:36.000Z",
  "fetched_at": "2026-07-29T05:10:12.205Z",
  "source_slug": "x-arxiv-cs-hc",
  "source_name": "arXiv cs.HC",
  "source_homepage": "https://arxiv.org/list/cs.HC/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/14439",
  "original_url": "https://arxiv.org/abs/2607.25968v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}