Communications of the ACM
Molecular, Neural and Bacterial Networks Provide Insights For Computer Network Security, Carnegie Mellon Researchers Find
Researchers in Carnegie Mellon University's Machine Learning Department say they can use the same defenses that yeast cells evolve to protect themselves to design computer networks and determine how secure they are.
Credit: Carnegie Mellon University
The robust defenses that yeast cells have evolved to protect themselves from environmental threats can be used to design computer networks and analyze how secure they are, say researchers at Carnegie Mellon University's (CMU) Machine Learning Department.
The researchers say they factored environmental "noise" into an established model for the evolution of molecular connections, which resulted in an algorithm that gives rise to a rich range of architectures found in biological, computer, and other types of networks. The approach is particularly helpful in understanding how networks respond to cascading failures, whether an overloaded power grid or a computer network being overwhelmed by fake identities in a Sybil attack.
The generative model the CMU team developed can be used to tailor networks to the environments in which they are expected to operate. The team modified the duplication-divergence model used to explain the evolution of molecular networks, which they used to develop a method than can be implemented to generate or evaluate the interconnection, or topology, of networks that work in a variety of environments.
From Carnegie Mellon News (PA)
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