An immunological model for detecting bot activities

Md E. Karim, Vir V. Phoha, Md A. Sultan

Research output: Chapter in Book/Entry/PoemConference contribution


We develop a hierarchical immunological model to detect bot activities in a computer network. In the proposed model antibody (detector)-antigen (foreign object) reactions are defined using negative selection based approach and negative systems-properties are defined by various temporal as well as non-temporal systems features. Theory of sequential hypothesis testing has been used in the literature for identifying spatial-temporal correlations among malicious remote hosts and among the bots within a botnet. We use it for combining multiple immunocomputing based decisions too. Negative selection based approach defines a self and helps identifying non-selves. We define non-selves with respect to various systems characteristics and then use different combinations of non-selves to design bot detectors. Each detector operates at the client sites of the network under surveillance. A match with any of the detectors suggests presence of a bot. Preliminary results suggest that the proposed model based solutions c n improve the identification of bot activities.

Original languageEnglish (US)
Title of host publicationIntelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing
StatePublished - 2009
Externally publishedYes
EventIntelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing - Orlando, FL, United States
Duration: Apr 15 2009Apr 17 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherIntelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing
Country/TerritoryUnited States
CityOrlando, FL


  • Botnet
  • Immunocomputing
  • Negative selection algorithm
  • Spatial-temporal correlation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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