{
  "id": 14459,
  "url": "https://arxiv.org/abs/2607.25430v1",
  "title": "SafeStats: Efficient 2PC Protocols for Data Statistic-Related Functions",
  "summary": "Statistical analysis on sensitive datasets like medical records and financial transactions is essential for decision-making, but raises significant privacy concerns. While existing secure Two-Party Computation (2PC) makes extensive efforts in designing the common secure primitives (e.g., addition and multiplication) or machine learning-related functions, few pay attention to the statistical functions. In this paper, we propose SafeStats, a secure toolkit tailored for 2PC secure statistical analy",
  "authors": "Tanren Liu, Xianjia Meng, Yang Liu, Xin Kang, Chenhui You, Yong Zeng, Zhuo Ma",
  "category": "research",
  "topics": "privacy-surveillance,healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-28T08:25:30.000Z",
  "fetched_at": "2026-07-29T05:10:12.205Z",
  "source_slug": "x-arxiv-cs-cr-ai-security",
  "source_name": "arXiv cs.CR (AI security)",
  "source_homepage": "https://arxiv.org/list/cs.CR/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/14459",
  "original_url": "https://arxiv.org/abs/2607.25430v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}