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Updated: Sep 18, 2025

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通过自适应性特征选择,用于不平衡的多类恶意软件分类的机器学习技术

Binayak Panda1, Sudhanshu Shekhar Bisoyi2, Sidhanta Panigrahy3

  • 1Department of Computer Science and Engineering, Institute of Technical Education and Research, Siksha 'O' Anusandhan (Deemed to be) University, Bhubaneswar, Odisha, India.

PeerJ. Computer science
|June 26, 2025
PubMed
概括

本研究引入了一个自适应多类恶意软件分类 (AMMC) 框架,具有自适应特征选择 (AFS),以有效检测恶意软件变体. 拟议的方法在多个数据集上取得了最先进的结果,提高了恶意软件检测性能.

关键词:
API序列的API序列是什么贪的功能选择选项机器学习 机器学习多类恶意软件分类多类恶意软件分类.跳过-克拉姆可以.国际货币基金组织-国际货币基金组织

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