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一个基于Kullback-Liebler分歧的表示算法用于恶意软件检测

Faitouri A Aboaoja1,2, Anazida Zainal3, Fuad A Ghaleb1

  • 1Faculty of Computing, Universiti Teknologi Malaysia, Johor Baru, Johor, Malaysia.

PeerJ. Computer science
|October 9, 2023
PubMed
概括

这项研究引入了一种新的算法,通过分析恶意软件和良性软件之间的行为差异来准确地分类恶意软件. 基于Kullback-Liebler分歧的术语频率概率类分布 (基于KLD的TF-PCD) 方法显著提高了恶意软件检测的准确性.

关键词:
躲避技术 躲避技术功能工程的特点工程.特性表示技术的特征表示技术.基于机器学习的恶意软件检测模型这是一种TF-IDF技术.

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