{
  "id": 827658,
  "title": "Concept Drift Detection and Adaptive Retraining of Malware Classification Models",
  "url": "https://urgent.news/2026/08/13/concept-drift-detection-and-adaptive-retraining-of-malware",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-08-13T16:46:56.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.13465v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Concept drift refers to changes over time in the statistical properties of data, as compared to the data that was used to train a learning model. Machine learning models for malware detection or classification are particularly susceptible to performance degradation caused by concept drift, as attackers constantly modify existing malware. In this chapter, we analyze two machine learning-based…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}