Nature-inspired algorithms have given us elegant solutions across a broad spectrum of design challenges. Efforts within cyber systems are equally replete with cases in which algorithms either adapted from, or at least inspired by, observations of natural biological systems, ranging from efficient packet routing, to anomaly detection, and beyond. We discuss how natural systems achieve robust and efficient solutions and the implications this ontology has for helping inform how and when it may be most fruitful to exploit them, and when instead we should probably forego analogy and instead build tailored tools from scratch. Further, we consider how it might be possible to move beyond this case-by-case analogy paradigm to exploit the deeper design elements that make natural systems successful at converging on sufficient solutions and then employ these more fundamental tools in purposeful design. In particular, we consider the design challenges faced when trying to borrow from nature to inform the areas of cyber security and resilience.

Chapter Contents:

• 2.1 Why natural systems are tempting
• 2.1.1 Analogous qualities in engineered cyber systems
• 2.2 How biological systems develop solutions
• 2.2.1 Darwinian evolution
• 2.2.1.1 Fitness
• 2.2.1.2 Competition
• 2.2.2 Avoiding a common trap: best may not be good
• 2.2.2.1 An illustrative example of evolution failing to converge on a single "best" solution
• 2.2.3 Does this make natural systems poor sources of inspiration?
• 2.3 Evidence of success from nature-inspired efforts
• 2.3.1 A standard pattern in nature-inspired design research
• 2.4 A few of nature's tools
• 2.4.1 Proximate cues
• 2.4.2 Distributed decisions
• 2.4.3 Error convergence
• 2.5 Synergy among nature's tools
• 2.6 Potential pitfalls in nature-inspired algorithms specific to cyber security and resilience
• 2.6.1 Coevolutionary arms races
• 2.6.2 Designed threats versus evolved threats
• 2.6.3 Trade-offs between security and privacy may be different for each design component
• 2.6.3.1 Proximate cues must be relatively "leak-proof"
• 2.6.3.2 Distributed decision-making
• 2.6.3.3 Error convergence
• 2.7 When NOT to use nature-inspired algorithms
• 2.8 Conclusions
• Acknowledgments
• References

Inspec keywords: security of data; biomimetics

Other keywords: anomaly detection; nature-inspired algorithms; natural biological systems; packet routing; cyber systems; resilience; cyber security; natural systems

Subjects: Data security