Fuzzy Anomaly Detection System for IPv6 (FADS6): An Immune-Inspired Algorithm with Hash Function

  • Yao Li
  • Zhitang Li
  • Li Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)


This paper presents a novel architecture for an immunological network anomaly detection system in IPv6 environment, Fuzzy Anomaly Detect System for IPv6 (FADS6). In order to perform the anomaly detection based on IPv6, it is necessary to develop more efficient anomaly detection rules generation technology, genetic algorithm is a good choice. A self-adaptive anomaly detection model was developed using fuzzy detection anomaly algorithm with negative selection of biology and proposed a fuzzy anomaly detection rules generation technology for IPv6 using genetic algorithm. In the proposed model, optimized the initial population with hash algorithm, encoded the population with random real values, and detected the anomaly with fuzzy detection rules. This model is flexible, extendible, and adaptable, can meet the needs, preferences of network administrators and supplied for IPv6 environment. Evaluated the model with CERNET2 backbone traffic, it showed that the model has two advantages: algorithm performance and detection effect, and can be applied to protect the next generation Internet.


Genetic Algorithm Hash Function Anomaly Detection Artificial Immune System Destination Address 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yao Li
    • 1
  • Zhitang Li
    • 1
  • Li Wang
    • 1
  1. 1.Network and Computer CenterHuazhong University of Science and TechnologyWuhanP.R. China

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