{"ID":2887799,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.00328","arxiv_id":"2508.00328","title":"From Patient Burdens to User Agency: Designing for Real-Time Protection Support in Online Health Consultations","abstract":"Online medical consultation platforms, while convenient, are undermined by significant privacy risks that erode user trust. We first conducted in-depth semi-structured interviews with 12 users to understand their perceptions of security and privacy landscapes on online medical consultation platforms, as well as their practices, challenges and expectation. Our analysis reveals a critical disconnect between users' desires for anonymity and control, and platform realities that offload the responsibility of ``privacy labor''. To bridge this gap, we present SafeShare, an interaction technique that leverages localized LLM to redact consultations in real-time. SafeShare balances utility and privacy through selectively anonymize private information. A technical evaluation of SafeShare's core PII detection module on 3 dataset demonstrates high efficacy, achieving 89.64\\% accuracy with Qwen3-4B on IMCS21 dataset.","short_abstract":"Online medical consultation platforms, while convenient, are undermined by significant privacy risks that erode user trust. We first conducted in-depth semi-structured interviews with 12 users to understand their perceptions of security and privacy landscapes on online medical consultation platforms, as well as their p...","url_abs":"https://arxiv.org/abs/2508.00328","url_pdf":"https://arxiv.org/pdf/2508.00328v1","authors":"[\"Shuning Zhang\",\"Ying Ma\",\"Yongquan `Owen' Hu\",\"Ting Dang\",\"Hong Jia\",\"Xin Yi\",\"Hewu Li\"]","published":"2025-08-01T05:21:42Z","proceeding":"cs.HC","tasks":"[\"cs.HC\"]","methods":"[\"Large Language Model\"]","has_code":false}