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  • 标题:Data Visualization Technique Framework for Intrusion detection
  • 本地全文:下载
  • 作者:Alaa El - Din Riad ; Ibrahim Elhenawy ; Ahmed Hassan
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2011
  • 卷号:8
  • 期号:5
  • 出版社:IJCSI Press
  • 摘要:Network attacks have become the fundamental threat to today\'s largely interconnected computer system. Intrusion detection system (IDS) is indispensable to defend the system in the face of increasing vulnerabilities. While a number of information visualization software frameworks exist, creating new visualizations, especially those that involve novel visualization metaphors, interaction techniques, data analysis strategies, and specialized rendering algorithms, is still often a difficult process. To facilitate the creation of novel visualizations this paper presents a new framework that is designed with using data visualization technique for analysis and visualizes snort result data for user. The framework suggests PHP and CSS as data visualization technique and snort as intrusion detection system (IDS).
  • 关键词:Intrusion Detection System; Visualization techniques; Snort; PHP and CSS
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