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An Artificial Immune System Approach for Artificial Chemistries Based on Set Rewriting

  • Daniel Schreckling
  • Tobias Marktscheffel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6209)

Abstract

An artificial immune system approach for artificial chemistries (ACs) based on set rewriting methods is introduced. We model signals which are generated by the execution of rewriting rules in the artificial chemistry. They induce signal patterns which trigger a system response. This response is also based on the rewriting rules of the AC. The latter inhibit or accelerate self-reproducing rewriting instructions and eliminate or inhibit non-self rewriting rules in the AC. Exemplarily, the developed artificial immune system model is integrated into the computational model of Fraglets, an AC which is based on multiset rewriting. Experimental results show the feasibility of this approach.

Keywords

Signal Pattern Negative Rule Signal Reactor Malicious Code Access Control Mechanism 
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 2010

Authors and Affiliations

  • Daniel Schreckling
    • 1
  • Tobias Marktscheffel
    • 1
  1. 1.Institute of IT-Security and Security LawUniversity of PassauPassauGermany

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