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Securing mobile ad hoc networks using danger theory-based artificial immune algorithm.

Maha Abdelhaq1, Raed Alsaqour1, Shawkat Abdelhaq2

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This study introduces the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in mobile ad hoc networks (MANETs). The MDCA effectively identifies resource consumption attacks, enhancing network security.

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Area of Science:

  • Computer Science
  • Network Security
  • Artificial Intelligence

Background:

  • Mobile ad hoc networks (MANETs) are decentralized, self-organizing networks vulnerable to attacks.
  • Flooding-based attacks are particularly dangerous, aiming to deplete network resources and cause paralysis.
  • Existing security measures require enhancement to address these threats effectively.

Purpose of the Study:

  • To investigate the efficacy of the mobile dendritic cell algorithm (MDCA) in detecting flooding-based attacks within MANETs.
  • To adapt the dendritic cell algorithm (DCA) for enhanced MANET security.
  • To introduce and simulate a novel resource consumption attack (RCA) module.

Main Methods:

  • Implementation and testing of the mobile dendritic cell algorithm (MDCA) in Qualnet v7.1.
  • Development of a new simulation module for resource consumption attacks (RCAs) in Qualnet v7.1.
  • Validation of MDCA's performance against flooding-based attacks.

Main Results:

  • The MDCA demonstrated high efficiency in detecting resource consumption attacks (RCAs).
  • The adapted DCA approach proved capable of securing MANET environments against flooding attacks.
  • Qualnet v7.1 simulations validated the effectiveness of the proposed MDCA.

Conclusions:

  • The mobile dendritic cell algorithm (MDCA) is a highly efficient method for detecting flooding-based attacks, specifically RCAs, in MANETs.
  • The MDCA offers a promising approach to bolstering the security of mobile ad hoc networks.
  • Further research can explore advanced applications of artificial immune algorithms in network defense.