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Bio-inspired Cyber Security for Communications and Networking

Feature Topic


Nature is Earth’s most amazing invention machine for solving problems and adapting to significant environmental changes. Its ability to address complex, large-scale problems with robust, adaptable, and efficient solutions results from many years of selection, genetic drift and mutations.  Thus, it is not surprising that inventors and researchers often look to natural systems for inspiration and methods for solving problems in human-created artificial environments.  This has resulted in the development of evolutionary algorithms including genetic algorithms and swarm algorithms, and of classifier and pattern-detection algorithms, such as neural networks, for solving hard computational problems.

A natural evolutionary driver is to survive long enough to create a next-generation of descendants and ensure their survival.  One factor in survival is an organism’s ability to defend against attackers, both predators and parasites, and against rapid changes in environmental conditions.  Analogously, networks and communications systems use cyber security to defend their assets against cyber criminals, hostile organizations, hackers, activists, and sudden changes in the network environment (e.g., DDoS attacks).  Many of the defense methods used by natural organisms may be mapped to cyber space to implement effective cyber security.  Some examples include immune systems, invader detection, friend vs. foe, camouflage, mimicry, evasion, etc.  Many cyber security technologies and systems in common use today have their roots in bio-inspired methods, including anti-virus, intrusion detection, threat behavior analysis, attribution, honeypots, counterattack, and the like.  As the threats evolve to evade current cyber security technologies, similarly the bio-inspired security and defense technologies evolve to counter the threat.

The goal of this feature topic is twofold: (1) to survey the current academic and industry research in bio-inspired cyber security for communications and networking, so that the ComSoc community can understand the current evolutionary state of cyber threats, defenses, and intelligence, and can plan for future transitions of the research into practical implementations; and (2) to survey current academic and industry system projects, prototypes, and deployed products and services (including threat intelligence services) that implement the next generation of bio-inspired methods.  Please note that we recognize that in some cases, details may be limited or obscured for security reasons.

Topics of interests include, but are not limited to:

  • Bio-inspired anomaly & intrusion detection
  • Adaptation algorithms for cyber security & networking
  • Biometrics related to cyber security & networking
  • Bio-inspired security and networking algorithms & technologies
  • Biomimetics related to cyber security & networking
  • Bio-inspired cyber threat intelligence methods and systems
  • Moving-target techniques
  • Network Artificial Immune Systems
  • Adaptive and Evolvable Systems
  • Neural networks, evolutionary algorithms, and genetic algorithms for cyber security & networking
  • Prediction techniques for cyber security & networking
  • Information hiding solutions (steganography, watermarking) and detection for network traffic
  • Cooperative defense systems
  • Bio-inspired algorithms for dependable networks


Wojciech Mazurczyk
Warsaw University of Technology

Sean Moore
Centripetal Networks

Errin W. Fulp
Wake Forest University

Hiroshi Wada

Kenji Leibnitz
National Institute of Information and Communications Technology