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通过使用机器学习模型的功能选择和扩展技术来增强恶意软件检测

Rakibul Hasan1, Barna Biswas2, Md Samiun3

  • 1Department of Business Administration, Westcliff University, 17877 Von Karman Ave 4th Floor, Irvine, CA, 92614, USA. r.hasan.179@westcliff.edu.

Scientific reports
|March 18, 2025
PubMed
概括

强大的恶意软件检测至关重要. 这项研究发现,集体机器学习模型,特别是光梯度增强机 (LGBM),结合主要组件分析 (PCA) 和缩放,在识别恶意软件方面实现了超过97%的准确性.

关键词:
深度学习是一种深度学习.功能扩展的扩展.机器学习 机器学习恶意软件检测 恶意软件检测主要组件分析的主要组件分析.

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