基于citespace的恶意代码检测态势研究分析
首发时间:2019-12-26
摘要:本文主要应用citespace可视化工具,基于文献关键词计量分析方法系统研究了在恶意代码检测领域的研究现状、研究热点以及研究态势。通过对发文量、研究机构、高产作者、关键词共现网络知识图谱的分析研究,发现目前国内恶意代码检测的研究处于增长阶段,以北京地区的研究成果居于首位;研究热点领域包括动态检测、静态检测和机器学习算法等;近几年的研究趋向偏向于深度学习方向。本文通过可视化方法为国内的恶意代码检测相关的研究者提供更系统的参考。
关键词: 网络安全 恶意代码 citespace 计量分析 态势
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Situation analysis of malicious code detection based on citespace
Abstract:This paper mainly uses the citespace visualization tool to systematically research the research status, research hotspots and research trends in the field of malicious code detection based on literature keyword measurement analysis methods. Through the analysis and research on the amount of posts, research institutions, high-yield authors, and keyword co-occurrence network knowledge maps, it is found that the current research on malicious code detection in China is in the growing stage, with research results in Beijing ranking first. Static detection and machine learning algorithms, etc ; research in recent years has tended to focus on deep learning.This paper provides a more systematic reference for domestic researchers related to malicious code detection through visualization methods.
Keywords: Network security malicious code citespace econometric analysis situation
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基于citespace的恶意代码检测态势研究分析
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