防火墙日志和入侵检测日志数据可视化系统的研究与应用

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
IET Software Pub Date : 2024-08-13 DOI:10.1049/2024/7060298
Ma Mingze
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引用次数: 0

摘要

本文针对当前网络安全分析面临的挑战,提出了一种创新的基于信息增益的特征选择算法,并利用可视化技术开发了一个网络安全日志数据可视化系统。该系统的主要功能包括防火墙日志和入侵检测日志的原始数据采集、数据预处理、数据库管理、数据操作、数据逻辑处理和数据可视化。通过对日志数据进行统计分析和构建可视化模型,该系统能以多种图形格式显示分析结果,同时提供交互功能。该系统将数据生成、处理、分析和显示过程无缝集成,在实验评估中分别达到了 98.3%、92.1%、97.5%、98.1% 和 91.2% 的高准确度、高精确度、高召回率、F1 分数和实时性能指标。所提出的方法大大提高了网络安全状态的实时预测能力和网络设备的监控效率,提供了一个强大的安全保障工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Research and Application of Firewall Log and Intrusion Detection Log Data Visualization System

Research and Application of Firewall Log and Intrusion Detection Log Data Visualization System

This paper tackles current challenges in network security analysis by proposing an innovative information gain-based feature selection algorithm and leveraging visualization techniques to develop a network security log data visualization system. The system’s key functions include raw data collection for firewall logs and intrusion detection logs, data preprocessing, database management, data manipulation, data logic processing, and data visualization. Through statistical analysis of log data and the construction of visualization models, the system presents analysis results in diverse graphical formats while offering interactive capabilities. Seamlessly integrating data generation, processing, analysis, and display processes, the system demonstrates high accuracy, precision, recall, F1 score, and real-time performance metrics, reaching 98.3%, 92.1%, 97.5%, 98.1%, and 91.2%, respectively, in experimental evaluations. The proposed method significantly enhances real-time prediction capabilities of network security status and monitoring efficiency of network devices, providing a robust security assurance tool.

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来源期刊
IET Software
IET Software 工程技术-计算机:软件工程
CiteScore
4.20
自引率
0.00%
发文量
27
审稿时长
9 months
期刊介绍: IET Software publishes papers on all aspects of the software lifecycle, including design, development, implementation and maintenance. The focus of the journal is on the methods used to develop and maintain software, and their practical application. Authors are especially encouraged to submit papers on the following topics, although papers on all aspects of software engineering are welcome: Software and systems requirements engineering Formal methods, design methods, practice and experience Software architecture, aspect and object orientation, reuse and re-engineering Testing, verification and validation techniques Software dependability and measurement Human systems engineering and human-computer interaction Knowledge engineering; expert and knowledge-based systems, intelligent agents Information systems engineering Application of software engineering in industry and commerce Software engineering technology transfer Management of software development Theoretical aspects of software development Machine learning Big data and big code Cloud computing Current Special Issue. Call for papers: Knowledge Discovery for Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_KDSD.pdf Big Data Analytics for Sustainable Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_BDASSD.pdf
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