Towards an Immunity-Based Anomaly Detection System for Network Traffic

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• 作者：Takeshi Okamoto ; Yoshiteru Ishida
• 刊名：Lecture Notes in Computer Science
• 出版年：2006
• 出版时间：2006
• 年：2006
• 卷：4252
• 期：1
• 页码：123-130
• 全文大小：186 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

We have applied our previous immunity-based system to anomaly detection for network traffic, and confirmed that our system outperformed the single-profile method. For internal masquerader detection, the missed alarm rate was 11.21% with no false alarms. For worm detection, four random-scanning worms and the simulated metaserver worm were detected with no missed alarms and no false alarms, while a simulated passive worm was detected with a missed alarm rate of 80.57%.