{
  "id": 12243,
  "url": "https://arxiv.org/abs/2607.17025v1",
  "title": "Federated Lightweight Intrusion Detection in Drone Swarms with Knowledge Distillation",
  "summary": "Drone swarms are increasingly deployed in critical applications such as surveillance, disaster response, and infrastructure monitoring. However, their reliance on open communication channels and their limited computational resources make them vulnerable to a wide range of cyber-threats. There is a growing interest in intrusion detection systems (IDS) specifically designed for drone environments and operations. However, the conventional solutions including Machine Learning (ML)-based approaches r",
  "authors": "Fawaz J. Alruwaili, Cihan Tunc",
  "category": "research",
  "topics": "privacy-surveillance,military-security,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-19T01:57:47.000Z",
  "fetched_at": "2026-07-21T05:10:12.656Z",
  "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/12243",
  "original_url": "https://arxiv.org/abs/2607.17025v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}