{
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  "@type": "article",
  "@id": "https://anchorfact.org/kb/network-intrusion-detection",
  "headline": "Network Intrusion Detection: AI-Powered Anomaly Detection and Zero-Day Threat Identification",
  "description": "Network Intrusion Detection Systems (NIDS) are the immune system of the internet — monitoring traffic for malicious activity. AI is transforming NIDS from signature-based pattern matching (misses novel attacks) to behavior-based anomaly detection that identifies zero-day threats, insider attacks, and advanced persistent threats by learning what \"normal\" network behavior looks like.",
  "dateCreated": "2026-05-24T02:49:13.641Z",
  "dateModified": "2026-05-24",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "Enhanced anomaly network intrusion detection via machine learning and deep learning models",
      "sameAs": "https://www.nature.com/articles/s41598-025-97398-1"
    },
    {
      "@type": "CreativeWork",
      "name": "A deep learning/machine learning approach for anomaly-based network intrusion detection (Hybrid NIDS)",
      "sameAs": "https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1625891/full"
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}