{
  "id": 12044,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1857306",
  "title": "Lightweight intrusion detection system using multiscale attention 1D CNN for large scale internet of things",
  "summary": "The Internet of Things (IoT) and its applications are increasing rapidly over the years. Due to the wide variety of IoT applications, cyber attackers are exploring strong attacking methods and patterns to damage the IoT networks in real-time applications even if the IoT network is secure. To protect the IoT networks, it is essential to design and develop a real-time intrusion detection system that can detect the attacking patterns and methods and prevent them immediately. To achieve this goal, w",
  "authors": "Dwarsala Sireesha",
  "category": "research",
  "topics": "military-security",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-20T00:00:00.000Z",
  "fetched_at": "2026-07-21T05:10:12.656Z",
  "source_slug": "x-frontiers-in-artificial-intelligence",
  "source_name": "Frontiers in Artificial Intelligence",
  "source_homepage": "https://www.frontiersin.org/journals/artificial-intelligence",
  "ethics_ai_record_url": "https://ethics.ai/record/12044",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1857306",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}